class_id | details | description | start_date | Venues | learning_levels | Topic | Tags | delivery_method | presenters | Organizer | seminar_series | class_title |
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1466 |
DescriptionDr. Stephanie Harmon obtained her Ph.D. in medical physics at the University of Wisconsin–Madison and did her postgraduate training at Leidos Biomedical Research where she worked within the Molecular Imaging Branch and investigated computational biomarkers in various state-of-the-art prostate imaging modalities. In 2020, she became a staff scientist within the newly formed Artificial Intelligence Resource of the NCI. Dr. Harmon’s research interests focus on computational approaches, including computer ...Read More Dr. Stephanie Harmon obtained her Ph.D. in medical physics at the University of Wisconsin–Madison and did her postgraduate training at Leidos Biomedical Research where she worked within the Molecular Imaging Branch and investigated computational biomarkers in various state-of-the-art prostate imaging modalities. In 2020, she became a staff scientist within the newly formed Artificial Intelligence Resource of the NCI. Dr. Harmon’s research interests focus on computational approaches, including computer vision and artificial intelligence, for combining multiscale biological and clinicopathological data to model cancer and cancer-related outcomes. She investigates the functional relationship of imaging characteristics across biological scales and their role in phenotypic heterogeneity in various cancer types. Her research centers around the idea that the use of integrative biomarkers from various imaging scales could enhance the understanding of disease and the role of imaging in cancer diagnosis and treatment. Her long-term goal is to identify interpretable imaging-based biomarkers on histopathological images that can predict underlying molecular phenotypes and translate these findings to improve diagnosis, treatment, and patient outcomes in various cancers. Dr. Harmon received many awards during her training, including the Prostate Cancer Foundation Young Investigator Award and the NCI Director’s Intramural Innovation Award. Dr. Harmon has published over 75 peer-reviewed articles, including publications in the Journal of Nuclear Medicine, PLOS One, JAMA Oncology, Cancer Imaging, Radiology, American Journal of Pathology, Journal of Medical Imaging, Nature Medicine, Journal of Clinical Oncology, Clinical Cancer Research, and Nature Communications. For more information, please contact Aniruddha Ganguly, Ph.D. Meeting number (access code): 2319 301 4914 Meeting password: KpxUgxg$372 DetailsOrganizerNCIWhenTue, Apr 23, 2024 - 9:30 am - 10:30 amWhereOnline |
Dr. Stephanie Harmon obtained her Ph.D. in medical physics at the University of Wisconsin–Madison and did her postgraduate training at Leidos Biomedical Research where she worked within the Molecular Imaging Branch and investigated computational biomarkers in various state-of-the-art prostate imaging modalities. In 2020, she became a staff scientist within the newly formed Artificial Intelligence Resource of the NCI. Dr. Harmon’s research interests focus on computational approaches, including computer vision and artificial intelligence, for combining multiscale biological and clinicopathological data to model cancer and cancer-related outcomes. She investigates the functional relationship of imaging characteristics across biological scales and their role in phenotypic heterogeneity in various cancer types. Her research centers around the idea that the use of integrative biomarkers from various imaging scales could enhance the understanding of disease and the role of imaging in cancer diagnosis and treatment. Her long-term goal is to identify interpretable imaging-based biomarkers on histopathological images that can predict underlying molecular phenotypes and translate these findings to improve diagnosis, treatment, and patient outcomes in various cancers. Dr. Harmon received many awards during her training, including the Prostate Cancer Foundation Young Investigator Award and the NCI Director’s Intramural Innovation Award. Dr. Harmon has published over 75 peer-reviewed articles, including publications in the Journal of Nuclear Medicine, PLOS One, JAMA Oncology, Cancer Imaging, Radiology, American Journal of Pathology, Journal of Medical Imaging, Nature Medicine, Journal of Clinical Oncology, Clinical Cancer Research, and Nature Communications. For more information, please contact Aniruddha Ganguly, Ph.D. Meeting number (access code): 2319 301 4914 Meeting password: KpxUgxg$372 | 2024-04-23 09:30:00 | Online | Any | AI,Image Analysis | Online | Stephanie A. Harmon (Molecular Imagin Branch CCR NCI) | NCI | 0 | Cancer Diagnosis Program Science Session Series: AI-Driven Imaging Biomarkers in Genitourinary Cancers | |
1464 |
DescriptionWhat’s the difference between “regular” statistics (i.e., what you may have been using in the past several years) and the “new” Bayesian statistics? Which one should you use for your next study? This is Part 1 of a two-part lecture series intended for non-statisticians interested in understanding the basic, intuitive thinking behind the two schools of statistical inference: frequentist (known as classical) and Bayesian. Part 1 will ...Read More What’s the difference between “regular” statistics (i.e., what you may have been using in the past several years) and the “new” Bayesian statistics? Which one should you use for your next study? This is Part 1 of a two-part lecture series intended for non-statisticians interested in understanding the basic, intuitive thinking behind the two schools of statistical inference: frequentist (known as classical) and Bayesian. Part 1 will address the frequentist approach and will cover the concepts of hypothesis testing, confidence intervals, Type I and Type II errors, statistical power, and p-values. Technical details will be kept to an absolute minimum. The class will be taught by the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES). Although you may attend only one part of this series, attending both parts will give you a better sense of the contrast between these two statistical approaches. During the class, time will be devoted to questions from attendees, and references will be provided for in-depth self-study. You must register separately for Part 2 of this class series. Individuals who need reasonable accommodations to participate should contact the NIH Interpreting Office directly at nih@ainterpreting.com, or the NIH Library Information Desk at 301-496-1080. Requests should be made at least five business days in advance in order to ensure availability. Details |
What’s the difference between “regular” statistics (i.e., what you may have been using in the past several years) and the “new” Bayesian statistics? Which one should you use for your next study? This is Part 1 of a two-part lecture series intended for non-statisticians interested in understanding the basic, intuitive thinking behind the two schools of statistical inference: frequentist (known as classical) and Bayesian. Part 1 will address the frequentist approach and will cover the concepts of hypothesis testing, confidence intervals, Type I and Type II errors, statistical power, and p-values. Technical details will be kept to an absolute minimum. The class will be taught by the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES). Although you may attend only one part of this series, attending both parts will give you a better sense of the contrast between these two statistical approaches. During the class, time will be devoted to questions from attendees, and references will be provided for in-depth self-study. You must register separately for Part 2 of this class series. Individuals who need reasonable accommodations to participate should contact the NIH Interpreting Office directly at nih@ainterpreting.com, or the NIH Library Information Desk at 301-496-1080. Requests should be made at least five business days in advance in order to ensure availability. | 2024-04-23 11:00:00 | Online | Any | Statistics | Online | Xiaobai Li | ORF/NIH Library | 0 | Statistical Inference - Frequentist Approach: Part 1 | |
1463 |
DescriptionCrunching of large data requires large resources. Exploration of holobiont metagenomes is considered a “big data” project and here I’ll be describing how I used the FRCE cluster to explore 794 metagenomes simultaneously to assess the biosynthetic capacity associated with lichens. This presentation will focus more on computational tools and techniques used to solve metagenomic problems. This presentation is aimed at beginner to intermediate users. A basic understanding of Bash and ...Read More Crunching of large data requires large resources. Exploration of holobiont metagenomes is considered a “big data” project and here I’ll be describing how I used the FRCE cluster to explore 794 metagenomes simultaneously to assess the biosynthetic capacity associated with lichens. This presentation will focus more on computational tools and techniques used to solve metagenomic problems. This presentation is aimed at beginner to intermediate users. A basic understanding of Bash and Slurm would be beneficial but not vital. This will be a hybrid event. This session will be recorded, and materials will be posted on the ABCS training site and also shared with attendees a few days after the event. For additional details and questions, please contact Natasha Pacheco (natasha.pacheco@nih.gov), Advanced Biomedical Computational Science group, Frederick National Laboratory for Cancer Research. DetailsOrganizerBACSWhenTue, Apr 23, 2024 - 12:00 pm - 1:00 pmWhereBuilding 549 Conference Room B, Frederick |
Crunching of large data requires large resources. Exploration of holobiont metagenomes is considered a “big data” project and here I’ll be describing how I used the FRCE cluster to explore 794 metagenomes simultaneously to assess the biosynthetic capacity associated with lichens. This presentation will focus more on computational tools and techniques used to solve metagenomic problems. This presentation is aimed at beginner to intermediate users. A basic understanding of Bash and Slurm would be beneficial but not vital. This will be a hybrid event. This session will be recorded, and materials will be posted on the ABCS training site and also shared with attendees a few days after the event. For additional details and questions, please contact Natasha Pacheco (natasha.pacheco@nih.gov), Advanced Biomedical Computational Science group, Frederick National Laboratory for Cancer Research. | 2024-04-23 12:00:00 | Building 549 Conference Room B, Frederick | Any | Big Data | Hybrid | Sam Waterworth Molecular Targets Program NCI | BACS | 0 | Practical use case of FRCE cluster utilities: Exploring the metagenome of 794 lichen holobionts | |
1472 |
DescriptionJoin Dr. Kai Tan of the Children’s Hospital of Philadelphia as he discusses his cutting-edge technology, CytoCommunity, for the supervised and unsupervised discovery of tissue cellular neighborhoods. CytoCommunity offers a powerful and scalable method for de novo interpretation of cellular function and cell-cell communications in tissue microenvironments. This event is part of the NCI Emerging ...Read More Join Dr. Kai Tan of the Children’s Hospital of Philadelphia as he discusses his cutting-edge technology, CytoCommunity, for the supervised and unsupervised discovery of tissue cellular neighborhoods. CytoCommunity offers a powerful and scalable method for de novo interpretation of cellular function and cell-cell communications in tissue microenvironments. This event is part of the NCI Emerging Technologies Seminar Series, which highlights novel, NCI-funded technologies working to transform cancer research and clinical care. DetailsOrganizerCBIITWhenTue, Apr 23, 2024 - 2:00 pm - 3:00 pmWhereOnline |
Join Dr. Kai Tan of the Children’s Hospital of Philadelphia as he discusses his cutting-edge technology, CytoCommunity, for the supervised and unsupervised discovery of tissue cellular neighborhoods. CytoCommunity offers a powerful and scalable method for de novo interpretation of cellular function and cell-cell communications in tissue microenvironments. This event is part of the NCI Emerging Technologies Seminar Series, which highlights novel, NCI-funded technologies working to transform cancer research and clinical care. | 2024-04-23 14:00:00 | Online | Any | AI | Online | Kai Tan (Children’s Hospital of Philadelphia) | CBIIT | 0 | Finding Neighborhoods in the Land of Spatial Omics | |
1469 |
DescriptionPlease join us on Wednesday, April 24, 2024, when Dr. Abhishek Jha, co-founder and CEO of Elucidata, will present " Data Quality for LLMs: Building a Reliable Data Foundation." The presentation starts at 11:00 a.m. ET and ends at noon. Please join us on Wednesday, April 24, 2024, when Dr. Abhishek Jha, co-founder and CEO of Elucidata, will present " Data Quality for LLMs: Building a Reliable Data Foundation." The presentation starts at 11:00 a.m. ET and ends at noon. • unstructured data from the public repository Gene Expression Omnibus. DetailsOrganizerCBIITWhenWed, Apr 24, 2024 - 11:00 am - 12:00 pmWhereOnline |
Please join us on Wednesday, April 24, 2024, when Dr. Abhishek Jha, co-founder and CEO of Elucidata, will present " Data Quality for LLMs: Building a Reliable Data Foundation." The presentation starts at 11:00 a.m. ET and ends at noon. If you use large language models (LLMs) in your cancer research, register for this seminar to hear Elucidata’s Dr. Abhishek Jha discuss how data quality impacts LLM performance. A reliable foundation that is well annotated and accessible to an LLM plays a major role in the value of its results. You’ll see examples of how LLM-powered artificial intelligence (AI) agents query across three versions of the same gene expression corpus with differing results, including: • unstructured data from the public repository Gene Expression Omnibus.• structured data from the Crowd Extracted Expression of Differential Signatures project.• clean, linked, and harmonized data. Dr. Jha will use these examples to discuss how the different quality in these data sources impacts LLM performance. | 2024-04-24 11:00:00 | Online | Any | AI,Data Management | Online | Dr. Abhishek Jha (Elucidata) | CBIIT | 0 | Data Quality for LLMs: Building a Reliable Data Foundation | |
1446 |
Getting Started with scRNA-Seq Seminar SeriesDescriptionThis seminar provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat. In this seminar, attendees will learn about options for analyzing scRNA-Seq data, resources for learning R, how to import scRNA-Seq data, and how to create, examine, and access data stored in a Seurat object. This seminar provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat. In this seminar, attendees will learn about options for analyzing scRNA-Seq data, resources for learning R, how to import scRNA-Seq data, and how to create, examine, and access data stored in a Seurat object. Register |
This seminar provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat. In this seminar, attendees will learn about options for analyzing scRNA-Seq data, resources for learning R, how to import scRNA-Seq data, and how to create, examine, and access data stored in a Seurat object. | 2024-04-24 13:00:00 | Online Webinar | Beginner | R programming,Single Cell Analysis,Single Cell RNA-Seq | R programming,Single Cell RNA-seq,Seurat | Online | Alex Emmons (BTEP) | BTEP | 1 | Introduction to scRNA-Seq with R (Seurat) |
1467 |
DescriptionDear Colleagues, Dear Colleagues, For questions contact Daoud Meerzaman or Kayla Strauss.
DetailsOrganizerCBIITWhenFri, Apr 26, 2024 - 10:00 am - 11:00 amWhereOnline |
Dear Colleagues, In this webinar, you'll get an introduction to WebMeV. WebMeV aims to democratize bioinformatics analysis for biological sciences researchers. The maturation of many bioinformatics processes in sequencing has enabled the standardization of protocols. This allows simple programmatic encapsulation of the analysis. New technology has also allowed increased accessibility and replication of the software environment itself. WebMeV provides both transparency and reproducibility of the analysis code and build environment. It also provides an easy to use web-based graphical interface to count-based bioinformatics analyses of RNASeq, scRNASeq, and more. For questions contact Daoud Meerzaman or Kayla Strauss. | 2024-04-26 10:00:00 | Online | Any | Bioinformatics Software,Genomics | Online | John Quackenbush (Harvard T.H. Chan School of Public Health) | CBIIT | 0 | Webinar on WebMeV: Web-based Software for Exploratory Next Generation Genomic Data Analysis | |
1440 |
DescriptionWebinar attendees will hear tips and tricks to code efficiently in the Researcher Workbench using R and RStudio. Although Python and SAS are alternative programming languages available on the Researcher Workbench, this session will only focus on using R and RStudio. Participants should already have a general understanding of how to code in R prior to attending the session. This session will not cover the basics of coding in R. Presenter:Read More Webinar attendees will hear tips and tricks to code efficiently in the Researcher Workbench using R and RStudio. Although Python and SAS are alternative programming languages available on the Researcher Workbench, this session will only focus on using R and RStudio. Participants should already have a general understanding of how to code in R prior to attending the session. This session will not cover the basics of coding in R. Presenter: Aymone Kouame is a Data Scientist at Vanderbilt University Medical Center. She leads the Data Science & Engineering efforts for Digital Health Technologies (Fitbit). She is involved in the back-end and front-end processes of the All of Us Researcher Workbench curated data repository, working closely with the Curation and the Research Support Teams. Aymone discovered her passion for Data Science after a few years working/studying in Business and Accounting. She holds Master Degrees of Science in Data Analytics, Information Systems, and Accounting and Business Management. Before VUMC, she worked on the Data Science team of a cyber security company. This is the fourth of five sessions about NIH’s All of Us Research Program and Researcher Workbench. Attendees are encouraged to attend all sessions. Register for additional session below:
For questions about this webinar series, contact Cindy Sheffield, cynthia.sheffield@nih.gov
DetailsOrganizerNIH LibraryWhenFri, Apr 26, 2024 - 11:00 am - 12:00 pmWhereOnline |
Webinar attendees will hear tips and tricks to code efficiently in the Researcher Workbench using R and RStudio. Although Python and SAS are alternative programming languages available on the Researcher Workbench, this session will only focus on using R and RStudio. Participants should already have a general understanding of how to code in R prior to attending the session. This session will not cover the basics of coding in R. Presenter: Aymone Kouame is a Data Scientist at Vanderbilt University Medical Center. She leads the Data Science & Engineering efforts for Digital Health Technologies (Fitbit). She is involved in the back-end and front-end processes of the All of Us Researcher Workbench curated data repository, working closely with the Curation and the Research Support Teams. Aymone discovered her passion for Data Science after a few years working/studying in Business and Accounting. She holds Master Degrees of Science in Data Analytics, Information Systems, and Accounting and Business Management. Before VUMC, she worked on the Data Science team of a cyber security company. This is the fourth of five sessions about NIH’s All of Us Research Program and Researcher Workbench. Attendees are encouraged to attend all sessions. Register for additional session below: Session 5 - May 3: Resources to Support Researchers For questions about this webinar series, contact Cindy Sheffield, cynthia.sheffield@nih.gov | 2024-04-26 11:00:00 | Online | Any | All of Us Research Program | Online | Aymone Kouame (Vanderbilt University Medical Center) | NIH Library | 0 | All of Us NIH Library Webinar Series: Session 4 - Introduction to Coding in the Researcher Workbench | |
1451 |
DescriptionWhat’s the difference between “regular” statistics (i.e., what you may have been using in the past several years) and the “new” Bayesian statistics? Which one should you use for your next study? This is Part 2 of a two-part lecture series intended for non-statisticians interested in understanding the basic, intuitive thinking behind the two schools of statistical inference: frequentist (known as classical) and Bayesian. Part 2 ...Read More What’s the difference between “regular” statistics (i.e., what you may have been using in the past several years) and the “new” Bayesian statistics? Which one should you use for your next study? This is Part 2 of a two-part lecture series intended for non-statisticians interested in understanding the basic, intuitive thinking behind the two schools of statistical inference: frequentist (known as classical) and Bayesian. Part 2 will address the Bayesian approach and will cover the concepts of Bayes’ Theorem, prior and posterior distributions, and Bayes factor. Technical details will be kept to an absolute minimum. This class will be taught by the Clinical Center's Biostatistics and Clinical Epidemiology Service (CC/BCES). Although you may attend only one part of this series, attending both parts will give you a better sense of the contrast between these two statistical approaches. During the class, time will be devoted to questions from attendees, and references will be provided for in-depth self-study. You must register separately for Part 1 of this class series. DetailsOrganizerNIH LibraryWhenTue, Apr 30, 2024 - 11:00 am - 12:30 pmWhereOnline |
What’s the difference between “regular” statistics (i.e., what you may have been using in the past several years) and the “new” Bayesian statistics? Which one should you use for your next study? This is Part 2 of a two-part lecture series intended for non-statisticians interested in understanding the basic, intuitive thinking behind the two schools of statistical inference: frequentist (known as classical) and Bayesian. Part 2 will address the Bayesian approach and will cover the concepts of Bayes’ Theorem, prior and posterior distributions, and Bayes factor. Technical details will be kept to an absolute minimum. This class will be taught by the Clinical Center's Biostatistics and Clinical Epidemiology Service (CC/BCES). Although you may attend only one part of this series, attending both parts will give you a better sense of the contrast between these two statistical approaches. During the class, time will be devoted to questions from attendees, and references will be provided for in-depth self-study. You must register separately for Part 1 of this class series. | 2024-04-30 11:00:00 | Online | Any | Data analysis,Statistics | Online | Nusrat Rabbee | NIH Library | 0 | Statistical Inference - Bayesian Concepts: Part 2 | |
1448 |
Getting Started with scRNA-Seq Seminar SeriesDescriptionThis lesson reviews many of the standard steps in a scRNA-Seq workflow: QC filtering, normalization, scaling, and clustering. This lesson reviews many of the standard steps in a scRNA-Seq workflow: QC filtering, normalization, scaling, and clustering. Register |
This lesson reviews many of the standard steps in a scRNA-Seq workflow: QC filtering, normalization, scaling, and clustering. | 2024-05-01 13:00:00 | Online Webinar | Beginner | Single Cell Analysis,Single Cell RNA-Seq | R programming,Single Cell RNA-seq | Online | Alex Emmons (BTEP) | BTEP | 1 | Getting Started with Seurat: QC to Clustering |
1473 |
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To register to attend, you must log in to your SITC Cancer Immunotherapy CONNECT account. Don’t have an account? Create a free one. Join Dr. Mullin of the Roswell Park Comprehensive Cancer Center and Dr. Bao of the UPMC Hillman Cancer Center as they talk about artificial intelligence’s (AI’s) role in real-time monitoring of patients who are receiving immunotherapy for immune-related adverse events (irAE). If you attend, you’ll learn about: the current application of AI in irAE monitoring and detection. future applications of these technologies across the field. This webinar is the first of the 2024 SITC-NCI Computational Immuno-oncology Webinar Series, which focuses on the application of AI in immuno-oncology. It consists of nine free webinars to help individual research labs overcome computational challenges while analyzing and integrating different assay data throughout the immuno-oncology spectrum using AI. The annual series aims to educate early-career scientists, increase participants’ awareness of and engagement in NCI-supported Cancer Moonshot℠ Immunotherapy Networks, and fulfill the Blue Ribbon Panel’s goal of accelerating progress in cancer research. | 2024-05-02 12:00:00 | Online | Any | AI | Online | Sarah Mullin (Roswell Park Comprehensive Cancer Center) Riyue Bao (UPMC Hillman Cancer Center) | CBIIT | 0 | Real-Time AI Monitoring & Early Detection of Immune-Related Adverse Events | |
1381 |
AI in Biomedical Research @ NIH Seminar SeriesDescriptionThe explosion of biomedical big data and information in the past decade or so has created new opportunities for discoveries to improve the treatment and prevention of human diseases. As such, the field of medicine is undergoing a paradigm shift driven by AI-powered analytical solutions. This talk explores the benefits (and risks) of AI and ChatGPT, highlighting their pivotal roles in revolutionizing biomedical discovery, patient care, diagnosis, treatment, and medical research. By ...Read More The explosion of biomedical big data and information in the past decade or so has created new opportunities for discoveries to improve the treatment and prevention of human diseases. As such, the field of medicine is undergoing a paradigm shift driven by AI-powered analytical solutions. This talk explores the benefits (and risks) of AI and ChatGPT, highlighting their pivotal roles in revolutionizing biomedical discovery, patient care, diagnosis, treatment, and medical research. By demonstrating their uses in some real-world applications such as improving biomedical literature searches (Nature Biotechnology 2018; Nature 2020; Nature Genetics 2023), accelerating patient trial matching (TrialGPT, in collaboration with NCI clinicians), and assisting gene set analysis (GeneAgent, in collaboration with NCI researchers), we underscore the potential of AI and ChatGPT in enhancing clinical decision-making, personalizing patient experiences, and accelerating knowledge discovery. Alternative Meeting Information: Meeting number: 2300 950 8025 Password: qiQsnDx?923 Join by video system Dial 23009508025@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2300 950 8025Register |
The explosion of biomedical big data and information in the past decade or so has created new opportunities for discoveries to improve the treatment and prevention of human diseases. As such, the field of medicine is undergoing a paradigm shift driven by AI-powered analytical solutions. This talk explores the benefits (and risks) of AI and ChatGPT, highlighting their pivotal roles in revolutionizing biomedical discovery, patient care, diagnosis, treatment, and medical research. By demonstrating their uses in some real-world applications such as improving biomedical literature searches (Nature Biotechnology 2018; Nature 2020; Nature Genetics 2023), accelerating patient trial matching (TrialGPT, in collaboration with NCI clinicians), and assisting gene set analysis (GeneAgent, in collaboration with NCI researchers), we underscore the potential of AI and ChatGPT in enhancing clinical decision-making, personalizing patient experiences, and accelerating knowledge discovery. Alternative Meeting Information: Meeting number: 2300 950 8025 Password: qiQsnDx?923 Join by video system Dial 23009508025@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2300 950 8025 | 2024-05-02 13:00:00 | Online Webinar | Any | AI,Text Mining | Online | Dr. Zhiyong Lu (NCBI) | BTEP | 1 | Transforming Medicine with AI: From TrialGPT to GeneAgent | |
1441 |
DescriptionWebinar attendees will learn how to use and navigate the All of Us Researcher Workbench’s User Support Hub, which provides video tutorials, help articles, and more. Attendees will also learn about opportunities to get support from the Researcher Workbench help desk and how to stay involved with the All of Us Research Program through the program’s network of partners. Presenters: Rubin Baskir, ...Read More Webinar attendees will learn how to use and navigate the All of Us Researcher Workbench’s User Support Hub, which provides video tutorials, help articles, and more. Attendees will also learn about opportunities to get support from the Researcher Workbench help desk and how to stay involved with the All of Us Research Program through the program’s network of partners. Presenters: Rubin Baskir, Ph.D., Researcher Engagement and Outreach Branch Chief, All of Us Research Program Sydney McMaster, CHES, Program Officer, All of Us Research Program This is the fifth of five sessions about NIH’s All of Us Research Program and Researcher Workbench. Attendees are encouraged, but not required, to attend all sessions. For questions about this webinar series, contact Cindy Sheffield, cynthia.sheffield@nih.gov
DetailsOrganizerNIH LibraryWhenFri, May 03, 2024 - 11:00 am - 12:00 pmWhereOnline |
Webinar attendees will learn how to use and navigate the All of Us Researcher Workbench’s User Support Hub, which provides video tutorials, help articles, and more. Attendees will also learn about opportunities to get support from the Researcher Workbench help desk and how to stay involved with the All of Us Research Program through the program’s network of partners. Presenters: Rubin Baskir, Ph.D., Researcher Engagement and Outreach Branch Chief, All of Us Research ProgramRubin Baskir, Ph.D., is a Program Officer and the Researcher Engagement and Outreach Branch Chief within the NIH All of Us Research Program engagement team. He is excited to be working with a team that helps maintain the essential relationship between the program, participants, and community partners. Prior to his current position, Baskir began working in the All of Us Research Program as part of an American Association for the Advancement of Science (AAAS) science and technology policy fellowship. His interest in health policy began during his graduate work at Vanderbilt University, where, in addition to researching mechanisms of disease and signal transduction, he gained an appreciation for the effects of policy on human health. Baskir received his doctorate in clinical and cellular biology from Vanderbilt University and his Bachelor’s degree in biology from Washington University in St. Louis. Sydney McMaster, CHES, Program Officer, All of Us Research ProgramAs a passionate health equity advocate, Sydney McMaster has served as a Program Officer and Researcher Engagement Specialist for the NIH All of Us Research Program for over two years. In this role, she functions as a liaison between the researcher community and the national program, offering support and technical assistance to researchers interested in studying the program’s dataset. Prior to this role, Sydney served as a Public Health Analyst with the Health Resources and Services Administration (HRSA) for three years. As a previous participant in a pathways internship program with HRSA, Sydney is passionate about supporting equitable pathways for diverse professionals interested in research and public health careers. This is the fifth of five sessions about NIH’s All of Us Research Program and Researcher Workbench. Attendees are encouraged, but not required, to attend all sessions. For questions about this webinar series, contact Cindy Sheffield, cynthia.sheffield@nih.gov | 2024-05-03 11:00:00 | Online | Any | All of Us Research Program | Online | Rubin Baskir and Sydney McMaster (All of Us Research Program) | NIH Library | 0 | All of Us NIH Library Webinar Series: Session 5 - Resources to Support Researchers | |
1474 |
DescriptionHave you been looking for ways to use artificial intelligence (AI) in clinical practice but not sure where to start? Attend this webinar for tips from Dr. Anant Madabhushi on applying AI in precision oncology. He’ll describe how AI can be affordable, easy to interpret, and help ensure more equitable care for every patient. Specifically, Dr. Madabhushi will discuss efforts by his group to develop AI-based approaches for measuring:
Have you been looking for ways to use artificial intelligence (AI) in clinical practice but not sure where to start? Attend this webinar for tips from Dr. Anant Madabhushi on applying AI in precision oncology. He’ll describe how AI can be affordable, easy to interpret, and help ensure more equitable care for every patient. Specifically, Dr. Madabhushi will discuss efforts by his group to develop AI-based approaches for measuring:
He’ll describe how biomarkers like these can help you predict how well a patient will respond to treatment, as well as monitor their response. Dr. Madabhushi has been on the forefront of translating lab-created technologies into clinical practice. He’s pioneered the use of AI in precision oncology, offering new solutions for diagnosing cancers (i.e., breast, prostate, lung) and predicting how patients will respond to cancer treatments, such as chemotherapy, immunotherapy, and protein inhibitors (i.e., cyclin-dependent kinase 4 and 6). The Cancer Imaging Program is part of NCI’s Division of Cancer Treatment & Diagnosis. The program hosts this monthly NCI Imaging Community Webinar Series for scientists and clinicians interested in advancing cancer imaging. If you want to learn about upcoming opportunities for engagement, interdisciplinary collaboration, and current research showcases, you can explore upcoming events on the webinar series’ webpage. Dr. Anant Madabhushi is the Robert W. Woodruff Professor of Biomedical Engineering and serves on the faculty of the departments of pathology, biomedical informatics, urology, radiation oncology, radiology and imaging sciences, global health and computer and information sciences, all at Emory University. He’s also a research career scientist at the Atlanta Veterans Administration Medical Center. And he’s director of the Emory Empathetic AI for Health Institute at Emory University. Dr. Madabhushi has authored more than 500 peer-reviewed scientific publications and holds (or has pending) over 200 patents in the areas of AI, radiomics, medical image analysis, computer-aided diagnosis, and computer vision. DetailsOrganizerCBIITWhenMon, May 06, 2024 - 1:00 pm - 2:00 pmWhereOnline |
Have you been looking for ways to use artificial intelligence (AI) in clinical practice but not sure where to start? Attend this webinar for tips from Dr. Anant Madabhushi on applying AI in precision oncology. He’ll describe how AI can be affordable, easy to interpret, and help ensure more equitable care for every patient. Specifically, Dr. Madabhushi will discuss efforts by his group to develop AI-based approaches for measuring: alterations in the immune architecture underlying diseases (i.e., collagen disorder) using AI and pathology images, and changes in tumor blood vessels (vessel tortuosity) using AI and radiologic scans. He’ll describe how biomarkers like these can help you predict how well a patient will respond to treatment, as well as monitor their response. Dr. Madabhushi has been on the forefront of translating lab-created technologies into clinical practice. He’s pioneered the use of AI in precision oncology, offering new solutions for diagnosing cancers (i.e., breast, prostate, lung) and predicting how patients will respond to cancer treatments, such as chemotherapy, immunotherapy, and protein inhibitors (i.e., cyclin-dependent kinase 4 and 6). The Cancer Imaging Program is part of NCI’s Division of Cancer Treatment & Diagnosis. The program hosts this monthly NCI Imaging Community Webinar Series for scientists and clinicians interested in advancing cancer imaging. If you want to learn about upcoming opportunities for engagement, interdisciplinary collaboration, and current research showcases, you can explore upcoming events on the webinar series’ webpage. Dr. Anant Madabhushi is the Robert W. Woodruff Professor of Biomedical Engineering and serves on the faculty of the departments of pathology, biomedical informatics, urology, radiation oncology, radiology and imaging sciences, global health and computer and information sciences, all at Emory University. He’s also a research career scientist at the Atlanta Veterans Administration Medical Center. And he’s director of the Emory Empathetic AI for Health Institute at Emory University. Dr. Madabhushi has authored more than 500 peer-reviewed scientific publications and holds (or has pending) over 200 patents in the areas of AI, radiomics, medical image analysis, computer-aided diagnosis, and computer vision. | 2024-05-06 13:00:00 | Online | Any | AI | Online | Anant Madabhushi (Emory University) | CBIIT | 0 | Affordable, Interpretable, and Equitable AI for Precision Oncology | |
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DescriptionMacros are ways to use code to substitute in a value, and using macros makes a code in SAS easier to read, easier to edit, less prone to errors, and often allows it to run more efficiently. This intermediate class will provide an overview of what is a macro and how macros work in SAS, including the macro facility. Examples of macro code will be made available to class participants for modification and ...Read More Macros are ways to use code to substitute in a value, and using macros makes a code in SAS easier to read, easier to edit, less prone to errors, and often allows it to run more efficiently. This intermediate class will provide an overview of what is a macro and how macros work in SAS, including the macro facility. Examples of macro code will be made available to class participants for modification and later use. DetailsOrganizerNIH LibraryWhenTue, May 07, 2024 - 10:00 am - 11:00 amWhereOnline |
Macros are ways to use code to substitute in a value, and using macros makes a code in SAS easier to read, easier to edit, less prone to errors, and often allows it to run more efficiently. This intermediate class will provide an overview of what is a macro and how macros work in SAS, including the macro facility. Examples of macro code will be made available to class participants for modification and later use. | 2024-05-07 10:00:00 | Online | Any | SAS | Online | SAS | NIH Library | 0 | Coding Macros in SAS | |
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DescriptionGalaxy is a scientific workflow, data integration, data analysis, and publishing platform that makes computational biology accessible to research scientists that do not have computer programming experience. This workshop will introduce RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis for expression profiling. The hands-on exercises will run on the Galaxy platform using Illumina paired-end RNA-seq data. The workshop will ...Read More Galaxy is a scientific workflow, data integration, data analysis, and publishing platform that makes computational biology accessible to research scientists that do not have computer programming experience. This workshop will introduce RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis for expression profiling. The hands-on exercises will run on the Galaxy platform using Illumina paired-end RNA-seq data. The workshop will be taught by NCI staff and is open to NIH and HHS staff. DetailsOrganizerNIH LibraryWhenTue, May 07, 2024 - 1:00 pm - 4:00 pmWhereOnline |
Galaxy is a scientific workflow, data integration, data analysis, and publishing platform that makes computational biology accessible to research scientists that do not have computer programming experience. This workshop will introduce RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis for expression profiling. The hands-on exercises will run on the Galaxy platform using Illumina paired-end RNA-seq data. The workshop will be taught by NCI staff and is open to NIH and HHS staff. | 2024-05-07 13:00:00 | Online | Any | RNA-Seq | Online | Daoud Meerzaman (CBIIT) | NIH Library | 0 | RNA-Seq Analysis Training | |
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DescriptionPresented as part of the Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE) Webinar Series Dr. Philip Lupo is a professor of pediatrics and hematology-oncology at Baylor ...Read More Presented as part of the Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE) Webinar Series Dr. Philip Lupo is a professor of pediatrics and hematology-oncology at Baylor College of Medicine. His lab focuses on the molecular epidemiology of pediatric disease and conditions. His areas of interest include understanding the risk of cancer among children with structural birth defects, determining inherited genes underlying susceptibility to rhabdomyosarcoma, phenomic and genomic studies of structural birth defects, and addressing disparities in acute lymphoblastic leukemia susceptibility and outcomes. In this webinar, Dr. Lupo will be presenting on leveraging population-based registries for genomic studies of pediatric cancer. For more information, contact Leah Mechanic. DetailsOrganizerNCIWhenTue, May 07, 2024 - 3:00 pm - 4:00 pmWhereOnline |
Presented as part of the Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE) Webinar Series Dr. Philip Lupo is a professor of pediatrics and hematology-oncology at Baylor College of Medicine. His lab focuses on the molecular epidemiology of pediatric disease and conditions. His areas of interest include understanding the risk of cancer among children with structural birth defects, determining inherited genes underlying susceptibility to rhabdomyosarcoma, phenomic and genomic studies of structural birth defects, and addressing disparities in acute lymphoblastic leukemia susceptibility and outcomes. In this webinar, Dr. Lupo will be presenting on leveraging population-based registries for genomic studies of pediatric cancer. For more information, contact Leah Mechanic. | 2024-05-07 15:00:00 | Online | Any | Cancer,Genomics | Online | Dr. Philip Lupo (Baylor College of Medicine) | NCI | 0 | Leveraging Population-Based Registries for Genomic Studies of Pediatric Cancer | |
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DescriptionIf you’re a researcher, clinician, informaticist, commercial partner, or policy maker interested in cancer data science, register to attend this Cancer Data Exchange Summit. You’ll have the opportunity to hear (and take part in) discussions around current opportunities and challenges with the following topics:
If you’re a researcher, clinician, informaticist, commercial partner, or policy maker interested in cancer data science, register to attend this Cancer Data Exchange Summit. You’ll have the opportunity to hear (and take part in) discussions around current opportunities and challenges with the following topics:
You can also help identify cancer-specific elements; develop implementation guides; and define requirements to build large language models for extracting data. The participant group will comprise researchers, clinicians, informatics/data scientists, patient advocates, standard-setting organizations (such as HL7/FHIR), policymakers, EHR vendors, and industry partners. Their collaborative efforts will focus on identifying current opportunities, challenges, and essential oncology-specific data requirements for the USCDI+ Cancer use cases (1) using real-world data to determine patient eligibility for clinical trials; (2) identifying immune-related adverse events; (3) enhancing the efficiency and timeliness of cancer registry data. DetailsOrganizerNCIWhenWed, May 08 - Thu, May 09, 2024 -10:00 am - 5:00 pmWhereNCI Shady Grove at 9609 Medical Center Drive, Rockville, MD 20850 |
If you’re a researcher, clinician, informaticist, commercial partner, or policy maker interested in cancer data science, register to attend this Cancer Data Exchange Summit. You’ll have the opportunity to hear (and take part in) discussions around current opportunities and challenges with the following topics: How to use a patient’s data to determine their eligibility for clinical trials How to identify and develop data standards to detect immune-related adverse events Ways to enhance the efficiency and timeliness of the collection of cancer registry data Ways to support patient access, interoperability, and data sharing You can also help identify cancer-specific elements; develop implementation guides; and define requirements to build large language models for extracting data. The participant group will comprise researchers, clinicians, informatics/data scientists, patient advocates, standard-setting organizations (such as HL7/FHIR), policymakers, EHR vendors, and industry partners. Their collaborative efforts will focus on identifying current opportunities, challenges, and essential oncology-specific data requirements for the USCDI+ Cancer use cases (1) using real-world data to determine patient eligibility for clinical trials; (2) identifying immune-related adverse events; (3) enhancing the efficiency and timeliness of cancer registry data. | 2024-05-08 10:00:00 | NCI Shady Grove at 9609 Medical Center Drive, Rockville, MD 20850 | Any | Cancer,Science | Hybrid | NCI | 0 | Cancer Research Data Exchange Summit | ||
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Getting Started with scRNA-Seq Seminar SeriesDescriptionThis seminar provides an overview of differential expression testing workflows with Seurat. This seminar provides an overview of differential expression testing workflows with Seurat. Register |
This seminar provides an overview of differential expression testing workflows with Seurat. | 2024-05-08 13:00:00 | Online Webinar | Any | Single Cell Analysis,Single Cell RNA-Seq | R programming,Seurat,Single Cell RNA-seq | Online | Nathan Wong (CCBR) | BTEP | 1 | Differential Expression Analysis with Seurat |
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This one-hour session will introduce attendees to the world of Artificial Intelligence (AI) as we explore the fundamentals, applications, and ethical considerations of this transformative technology. Key topics will include machine learning, deep learning, data handling, and real-world AI applications across various industries. We'll delve into the ethical implications of AI and offer insights on how to become AI literate. Whether you're a seasoned professional or just starting your AI journey, this session will equip you with essential knowledge to navigate the AI landscape effectively and make informed decisions in our data-driven world. | 2024-05-08 13:00:00 | Online | Beginner | AI | Online | Alicia Lillich (NIH Library) | NIH Library | 0 | AI Literacy: Navigating the World of Artificial Intelligence | |
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DescriptionThis is the first class in the NIH Library Introduction to R Series. This class provides a basic overview of the functionality of R programming language and RStudio. R is a programming language and open source environment for statistical computing and graphics. The R class series is a comprehensive collection of training sessions offered by the NIH Library Data Services ...Read More This is the first class in the NIH Library Introduction to R Series. This class provides a basic overview of the functionality of R programming language and RStudio. R is a programming language and open source environment for statistical computing and graphics. The R class series is a comprehensive collection of training sessions offered by the NIH Library Data Services and Bioinformatics programs that is designed to teach non-programmers how to write modular code and to introduce best practices for using R for data analysis and data visualization. Each class uses both evidence-based best practices for programming and practical hands-on lessons. By the end of this class, students should be able to: list reasons for using R; describe the purpose of the RStudio Script, Console, Environment, and Plots panes; describe the various methods for finding help on R and RStudio; organize files and directories for a set of analyses as an R Project; define the following terms as they relate to R: object, assign, comment, call, function, and arguments; and assign values to objects in R. Students are encouraged to install R and RStudio before the class so that they can follow along with the instructor. Please bring your laptop with R and RStudio installed. DetailsOrganizerNIH LibraryWhenThu, May 09, 2024 - 11:00 am - 12:00 pmWhereOnline |
This is the first class in the NIH Library Introduction to R Series. This class provides a basic overview of the functionality of R programming language and RStudio. R is a programming language and open source environment for statistical computing and graphics. The R class series is a comprehensive collection of training sessions offered by the NIH Library Data Services and Bioinformatics programs that is designed to teach non-programmers how to write modular code and to introduce best practices for using R for data analysis and data visualization. Each class uses both evidence-based best practices for programming and practical hands-on lessons. By the end of this class, students should be able to: list reasons for using R; describe the purpose of the RStudio Script, Console, Environment, and Plots panes; describe the various methods for finding help on R and RStudio; organize files and directories for a set of analyses as an R Project; define the following terms as they relate to R: object, assign, comment, call, function, and arguments; and assign values to objects in R. Students are encouraged to install R and RStudio before the class so that they can follow along with the instructor. Please bring your laptop with R and RStudio installed. | 2024-05-09 11:00:00 | Online | Any | R programming | Online | Joelle Mornini (NIH Library) | NIH Library | 0 | Introduction to R and RStudio | |
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DescriptionThis in-person workshop will focus on data wrangling using tidy data principles. Tidy data describes a standard way of storing data that facilitates analysis and visualization within the tidyverse ecosystem. There will be a discussion of what makes data "tidy," and methods for reshaping your data using Read More This in-person workshop will focus on data wrangling using tidy data principles. Tidy data describes a standard way of storing data that facilitates analysis and visualization within the tidyverse ecosystem. There will be a discussion of what makes data "tidy," and methods for reshaping your data using dplyr and tidyr functions. Prior to attending this class, you will need to have:
By the end of this class, attendees will be able to demonstrate how to describe the purpose of the dplyr and tidyr packages, select certain columns in a data frame, select certain rows in a data frame according to filtering conditions, and add new columns to a data frame that are functions of existing columns. Note on TechnologyThe NIH Library has 24 pre-configured Windows laptops that you are welcome to use during this training on a first come, first served basis. You are also welcome to bring your own laptop (PC or Mac). NIH Staff bringing their own NIH-laptop can easily connect to the staff Wi-Fi. If participants are bringing a personal laptop, they are restricted to using the NIH-Guest-Network Wi-Fi. Registrants will receive an email with information and instructions to install and verify access to R and RStudio before the class. If you register the day before the class, you may not have time to download and properly install the necessary software. If you do not have the software installed, this training will be demo only. DetailsOrganizerNIH LibraryWhenMon, May 13, 2024 - 10:00 am - 12:00 pmWhereOnline |
This in-person workshop will focus on data wrangling using tidy data principles. Tidy data describes a standard way of storing data that facilitates analysis and visualization within the tidyverse ecosystem. There will be a discussion of what makes data "tidy," and methods for reshaping your data using dplyr and tidyr functions. Prior to attending this class, you will need to have: Installed R and RStudio Taken the Introduction to R and RStudio class. If not, here are some resources for getting started: Introduction to R Introduction to RStudio Introduction to Scripts in RStudio By the end of this class, attendees will be able to demonstrate how to describe the purpose of the dplyr and tidyr packages, select certain columns in a data frame, select certain rows in a data frame according to filtering conditions, and add new columns to a data frame that are functions of existing columns. Note on Technology The NIH Library has 24 pre-configured Windows laptops that you are welcome to use during this training on a first come, first served basis. You are also welcome to bring your own laptop (PC or Mac). NIH Staff bringing their own NIH-laptop can easily connect to the staff Wi-Fi. If participants are bringing a personal laptop, they are restricted to using the NIH-Guest-Network Wi-Fi. Registrants will receive an email with information and instructions to install and verify access to R and RStudio before the class. If you register the day before the class, you may not have time to download and properly install the necessary software. If you do not have the software installed, this training will be demo only. | 2024-05-13 10:00:00 | Online | Any | Data Wrangling | Online | Doug Joubert (NIH Library),Joelle Mornini (NIH Library) | NIH Library | 0 | Data Wrangling Workshop | |
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DescriptionParticipants will learn how to develop artificial intelligence (AI) applications using MATLAB, even if they do not have a formal background in machine and deep learning. The goal of this course is to introduce tools and fundamental approaches for developing predictive models on biomedical signals. The course will cover the entire AI pipeline, from signal exploration to deployment, including: annotating time series biomedical signals automatically, creating deep learning models using Convolutional Neural Networks (CNNs) ...Read More Participants will learn how to develop artificial intelligence (AI) applications using MATLAB, even if they do not have a formal background in machine and deep learning. The goal of this course is to introduce tools and fundamental approaches for developing predictive models on biomedical signals. The course will cover the entire AI pipeline, from signal exploration to deployment, including: annotating time series biomedical signals automatically, creating deep learning models using Convolutional Neural Networks (CNNs) and Long Short-Term Memories (LSTMs) for biomedical signal data, creating machine learning models for biomedical signal data, applying advanced signal pre-processing techniques for automated feature extraction, and automatically generating code for edge deployment of AI models. This is an introductory level class. No installation of MATLAB is necessary. DetailsOrganizerNIH LibraryWhenTue, May 14, 2024 - 1:00 pm - 2:30 pmWhereOnline |
Participants will learn how to develop artificial intelligence (AI) applications using MATLAB, even if they do not have a formal background in machine and deep learning. The goal of this course is to introduce tools and fundamental approaches for developing predictive models on biomedical signals. The course will cover the entire AI pipeline, from signal exploration to deployment, including: annotating time series biomedical signals automatically, creating deep learning models using Convolutional Neural Networks (CNNs) and Long Short-Term Memories (LSTMs) for biomedical signal data, creating machine learning models for biomedical signal data, applying advanced signal pre-processing techniques for automated feature extraction, and automatically generating code for edge deployment of AI models. This is an introductory level class. No installation of MATLAB is necessary. | 2024-05-14 13:00:00 | Online | Any | AI | Online | Mathworks | NIH Library | 0 | Data Science and Artificial Intelligence: Signals and Time Series Datasets Using MATLAB | |
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Description
To register to attend, you must log in to your SITC Cancer Immunotherapy CONNECT account. Don’t have an account? Create a free one.
Join Dr. Karchin of the Johns Hopkins School of Medicine and Dr. Krieg of the Medical University of South Carolina as they discuss the novel use of artificial intelligence (AI) in immunotherapy ...Read More
To register to attend, you must log in to your SITC Cancer Immunotherapy CONNECT account. Don’t have an account? Create a free one.
Join Dr. Karchin of the Johns Hopkins School of Medicine and Dr. Krieg of the Medical University of South Carolina as they discuss the novel use of artificial intelligence (AI) in immunotherapy target discovery. Attend this webinar to learn how:
This webinar is part of the 2024 SITC-NCI Computational Immuno-oncology Webinar Series, which focuses on the application of AI in immuno-oncology. This is the second of nine free webinars to help individual research labs overcome computational challenges while analyzing and integrating different assay data throughout the immuno-oncology spectrum using AI. The annual series aims to educate early-career scientists, increase participants’ awareness of and engagement in NCI-supported Cancer Moonshot℠ Immunotherapy Networks, and fulfill the Blue Ribbon Panel’s goal of accelerating progress in cancer research. DetailsOrganizerCBIITWhenWed, May 15, 2024 - 12:00 pm - 1:00 pmWhereOnline |
To register to attend, you must log in to your SITC Cancer Immunotherapy CONNECT account. Don’t have an account? Create a free one. Join Dr. Karchin of the Johns Hopkins School of Medicine and Dr. Krieg of the Medical University of South Carolina as they discuss the novel use of artificial intelligence (AI) in immunotherapy target discovery. Attend this webinar to learn how: AI advances could quickly improve clinical care. you can use AI to better analyze large-scale data sets for biomarkers that can enhance immunotherapy research. This webinar is part of the 2024 SITC-NCI Computational Immuno-oncology Webinar Series, which focuses on the application of AI in immuno-oncology. This is the second of nine free webinars to help individual research labs overcome computational challenges while analyzing and integrating different assay data throughout the immuno-oncology spectrum using AI. The annual series aims to educate early-career scientists, increase participants’ awareness of and engagement in NCI-supported Cancer Moonshot℠ Immunotherapy Networks, and fulfill the Blue Ribbon Panel’s goal of accelerating progress in cancer research. | 2024-05-15 12:00:00 | Online | Any | AI | Online | Rachel Karchin (Johns Hopkins School of Medicine) Carsten Krieg (Medical University of South Carolina) | CBIIT | 0 | AI in Personalized Immunotherapies | |
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DescriptionGeneralist repositories offer NIH researchers a flexible, trusted resource to share data for which there is no appropriate discipline specific repository as well as to share many other research outputs valuable for reproducibility and open science. This webinar, presented by participants of the NIH Generalist Repository Ecosystem Initiative (GREI) (Dataverse, Dryad, Figshare, Mendeley Data, Open Science Framework, Vivli, and Zenodo) will share generalist repository use cases and best practices for sharing and finding data ...Read More Generalist repositories offer NIH researchers a flexible, trusted resource to share data for which there is no appropriate discipline specific repository as well as to share many other research outputs valuable for reproducibility and open science. This webinar, presented by participants of the NIH Generalist Repository Ecosystem Initiative (GREI) (Dataverse, Dryad, Figshare, Mendeley Data, Open Science Framework, Vivli, and Zenodo) will share generalist repository use cases and best practices for sharing and finding data in generalist repositories. It will describe how generalist repositories fit into the NIH data repository landscape for intramural researchers and can be part of meeting the new NIH Data Management and Sharing Policy requirements. It will present both the key common features of generalist repositories that meet the NIH desirable repository characteristics as well as the unique features of these repositories that make them suited to specific types of data. DetailsOrganizerNIH LibraryWhenWed, May 15, 2024 - 1:00 pm - 2:00 pmWhereOnline |
Generalist repositories offer NIH researchers a flexible, trusted resource to share data for which there is no appropriate discipline specific repository as well as to share many other research outputs valuable for reproducibility and open science. This webinar, presented by participants of the NIH Generalist Repository Ecosystem Initiative (GREI) (Dataverse, Dryad, Figshare, Mendeley Data, Open Science Framework, Vivli, and Zenodo) will share generalist repository use cases and best practices for sharing and finding data in generalist repositories. It will describe how generalist repositories fit into the NIH data repository landscape for intramural researchers and can be part of meeting the new NIH Data Management and Sharing Policy requirements. It will present both the key common features of generalist repositories that meet the NIH desirable repository characteristics as well as the unique features of these repositories that make them suited to specific types of data. | 2024-05-15 13:00:00 | Online | Any | Data Management and Sharing | Online | Ana Van Gulick (FigShare) | NIH Library | 0 | Data Sharing: Generalist Repositories Ecosystem Initiative | |
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DescriptionThis course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing. This is an introductory two-part course for those who want to learn about ...Read More This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing. This is an introductory two-part course for those who want to learn about research data management and sharing, or for those who are interested in a refresher. Part 1 of this training will cover understanding research data, how to manage research data, and how to work with data. Audience: Researchers, fellows, post-docs, and trainees. You must register separately for Part 2 of this class. DetailsOrganizerNIH LibraryWhenThu, May 16, 2024 - 12:00 pm - 1:00 pmWhereOnline |
This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing. This is an introductory two-part course for those who want to learn about research data management and sharing, or for those who are interested in a refresher. Part 1 of this training will cover understanding research data, how to manage research data, and how to work with data. Audience: Researchers, fellows, post-docs, and trainees. You must register separately for Part 2 of this class. | 2024-05-16 12:00:00 | Online | Any | Data Management and Sharing | Online | Raisa Ionin (NIH Library) | NIH Library | 0 | Data Management and Sharing: Part 1 | |
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DescriptionQiagen CLC Genomics Workbench is a point-and-click bioinformatics software that runs on a personal computer and enables bulk RNA sequencing, ChIP sequencing, long reads, and variant analysis. This software is available to NCI scientists. This hands-on training will guide participants through bulk RNA sequencing analysis using CLC Genomics Workbench. After the class, participants will be able to
Qiagen CLC Genomics Workbench is a point-and-click bioinformatics software that runs on a personal computer and enables bulk RNA sequencing, ChIP sequencing, long reads, and variant analysis. This software is available to NCI scientists. This hands-on training will guide participants through bulk RNA sequencing analysis using CLC Genomics Workbench. After the class, participants will be able to
To get the most of this hands-on session, please reach out to the NCI service desk (https://service.cancer.gov/ncisp) to get this software installed, preview the tutorial (https://resources.qiagenbioinformatics.com/tutorials/RNASeq-droso.pdf), and download the example dataset (http://resources.qiagenbioinformatics.com/testdata/RNA_Seq_Droso2.zip) prior to attending. Meeting link: Join by video system Join by phone RegisterWhereOnline Webinar |
Qiagen CLC Genomics Workbench is a point-and-click bioinformatics software that runs on a personal computer and enables bulk RNA sequencing, ChIP sequencing, long reads, and variant analysis. This software is available to NCI scientists. This hands-on training will guide participants through bulk RNA sequencing analysis using CLC Genomics Workbench. After the class, participants will be able to Import files and illumina reads Import and associate metadata with samples Download reference genome and annotation Obtain RNA sequencing expression counts and perform differential expression analysis Construct PCA and heatmap to visualize RNA sequencing data To get the most of this hands-on session, please reach out to the NCI service desk (https://service.cancer.gov/ncisp) to get this software installed, preview the tutorial (https://resources.qiagenbioinformatics.com/tutorials/RNASeq-droso.pdf), and download the example dataset (http://resources.qiagenbioinformatics.com/testdata/RNA_Seq_Droso2.zip) prior to attending. Meeting link:https://cbiit.webex.com/cbiit/j.php?MTID=m07f826d16b67d3c3b8a86e275ebac5a5Meeting number:2300 281 6121Password:e7aEqhpy@34 Join by video systemDial 23002816121@cbiit.webex.comYou can also dial 173.243.2.68 and enter your meeting number. Join by phone1-650-479-3207 Call-in number (US/Canada)Access code: 2300 281 6121 | 2024-05-16 13:00:00 | Online Webinar | Any | Bioinformatics Software,Bulk RNA-Seq | Bioinformatics Software,Bulk RNA-seq | Online | Joe Wu (BTEP),Shawn Prince (Qiagen) | 0 | Qiagen CLC Genomics Workbench: bulk RNA sequencing | |
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DescriptionThe NIH Artificial Intelligence (AI) Symposium will take place on Friday, May 17th, 2024, in Masur Auditorium in Building 10 on the Bethesda NIH campus. This event is open to all NIH members - registration and abstract submission are now open https://forms.microsoft.com/g/4WpdBXcEu6 Biomedical science is in a technological revolution, driven by innovations in deep learning architecture and computational power. These ...Read More The NIH Artificial Intelligence (AI) Symposium will take place on Friday, May 17th, 2024, in Masur Auditorium in Building 10 on the Bethesda NIH campus. This event is open to all NIH members - registration and abstract submission are now open https://forms.microsoft.com/g/4WpdBXcEu6 Biomedical science is in a technological revolution, driven by innovations in deep learning architecture and computational power. These cutting-edge techniques are being applied to every sub-field of the biological sciences, and with ground-breaking advancements arriving constantly it is challenging for researchers to stay up to speed on what is possible. This one-day NIH AI Symposium will bring together researchers from a broad range of disciplines to share their AI-related research, with the goal of disseminating the newest AI research, providing an opportunity to network, and to cross-pollinate ideas across disciplines in order to advance AI research in biomedicine. Keynote speakers James Zou, Ph.D. (Stanford University) and Hari Shroff, Ph.D. (Janelia Research Campus) will share their research, and also participate in a Panel Discussion on the current and future potential of AI in biomedical sciences. There will also be short talks and posters from researchers on campus who are developing or using AI approaches. The NIH AI Symposium is sponsored by NHLBI, in partnership with FAES. Registration and abstract submission are open to all NIH members, including experts in AI-related fields and novices interested in gaining more exposure. Important dates: March 15th - Abstract submission deadline April 5th - Abstract notifications May 3rd – Registration deadline Sign language interpreting and CART services are available upon request to participate in this event. Individuals needing either of these services and/or other reasonable accommodations should contact Ryan O’Neill (oneillrs@nih.gov). Questions can be directed to Lead Organizer Ryan O’Neill, Ph.D. (oneillrs@nih.gov). DetailsOrganizerNHLBIWhenFri, May 17, 2024 - 9:00 am - 5:30 pmWhereMain NIH Campus, Building 10 (Clinical Center); Masur Auditorium |
The NIH Artificial Intelligence (AI) Symposium will take place on Friday, May 17th, 2024, in Masur Auditorium in Building 10 on the Bethesda NIH campus. This event is open to all NIH members - registration and abstract submission are now open https://forms.microsoft.com/g/4WpdBXcEu6 Biomedical science is in a technological revolution, driven by innovations in deep learning architecture and computational power. These cutting-edge techniques are being applied to every sub-field of the biological sciences, and with ground-breaking advancements arriving constantly it is challenging for researchers to stay up to speed on what is possible. This one-day NIH AI Symposium will bring together researchers from a broad range of disciplines to share their AI-related research, with the goal of disseminating the newest AI research, providing an opportunity to network, and to cross-pollinate ideas across disciplines in order to advance AI research in biomedicine. Keynote speakers James Zou, Ph.D. (Stanford University) and Hari Shroff, Ph.D. (Janelia Research Campus) will share their research, and also participate in a Panel Discussion on the current and future potential of AI in biomedical sciences. There will also be short talks and posters from researchers on campus who are developing or using AI approaches. The NIH AI Symposium is sponsored by NHLBI, in partnership with FAES. Registration and abstract submission are open to all NIH members, including experts in AI-related fields and novices interested in gaining more exposure. Important dates: March 15th - Abstract submission deadline April 5th - Abstract notifications May 3rd – Registration deadline Sign language interpreting and CART services are available upon request to participate in this event. Individuals needing either of these services and/or other reasonable accommodations should contact Ryan O’Neill (oneillrs@nih.gov). Questions can be directed to Lead Organizer Ryan O’Neill, Ph.D. (oneillrs@nih.gov). | 2024-05-17 09:00:00 | Main NIH Campus, Building 10 (Clinical Center); Masur Auditorium | Any | AI | In-Person | James Zou (Stanford University) Hari Shroff (Janelia Research Campus) | NHLBI | 0 | NIH Artificial Intelligence Symposium | |
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DescriptionThis course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing. This is an introductory two-part course for those who want to learn about ...Read More This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing. This is an introductory two-part course for those who want to learn about research data management and sharing, or for those who are interested in a refresher. During Part 2 of this training, participants will learn about sharing and archiving data. Audience: Researchers, fellows, post-docs, and trainees. You must register separately for Part 1 of this class. DetailsOrganizerNIH LibraryWhenFri, May 17, 2024 - 12:00 pm - 1:00 pmWhereOnline |
This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing. This is an introductory two-part course for those who want to learn about research data management and sharing, or for those who are interested in a refresher. During Part 2 of this training, participants will learn about sharing and archiving data. Audience: Researchers, fellows, post-docs, and trainees. You must register separately for Part 1 of this class. | 2024-05-17 12:00:00 | Online | Any | Data Management and Sharing | Online | Raisa Ionin (NIH Library) | NIH Library | 0 | Data Management and Sharing: Part 2 | |
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DescriptionHybrid (in-person location in Rockville, MD) Virtual attending via WebEx Meeting, link will be available two weeks prior to the meeting date. Attend the 2024 Co-Clinical Imaging Research Resource Program (CIRP) Annual Hybrid Meeting to learn about optimized quantitative imaging methods in cancer research and precision oncology. Register ...Read More Hybrid (in-person location in Rockville, MD) Virtual attending via WebEx Meeting, link will be available two weeks prior to the meeting date. Attend the 2024 Co-Clinical Imaging Research Resource Program (CIRP) Annual Hybrid Meeting to learn about optimized quantitative imaging methods in cancer research and precision oncology. Register by 11:00 p.m. ET, May 6. You’ll hear from presenters about optimizing quantitative imaging methods to improve the quality of imaging results for co-clinical cancer trials. You’ll also learn about applications of co-clinical imaging to precision oncology. There will be poster presentations, demonstrations, and discussions. The CIRP network is a joint effort of the Cancer Imaging Program at the Division of Cancer Treatment and Diagnosis, the Division of Cancer Biology, and the Division of Cancer Prevention. CIRP’s mission is to advance precision medicine by establishing best practices for co-clinical imaging. CIRP also seeks to develop optimized translational quantitative imaging methodologies to advance cancer research and treatment. DetailsOrganizerCBIITWhenMon, May 20 - Tue, May 21, 2024 -9:00 am - 4:00 pmWhere9609 Medical Center Drive, Rockville, MD, 20850 |
Hybrid (in-person location in Rockville, MD) Virtual attending via WebEx Meeting, link will be available two weeks prior to the meeting date. Attend the 2024 Co-Clinical Imaging Research Resource Program (CIRP) Annual Hybrid Meeting to learn about optimized quantitative imaging methods in cancer research and precision oncology. Register by 11:00 p.m. ET, May 6. You’ll hear from presenters about optimizing quantitative imaging methods to improve the quality of imaging results for co-clinical cancer trials. You’ll also learn about applications of co-clinical imaging to precision oncology. There will be poster presentations, demonstrations, and discussions. The CIRP network is a joint effort of the Cancer Imaging Program at the Division of Cancer Treatment and Diagnosis, the Division of Cancer Biology, and the Division of Cancer Prevention. CIRP’s mission is to advance precision medicine by establishing best practices for co-clinical imaging. CIRP also seeks to develop optimized translational quantitative imaging methodologies to advance cancer research and treatment. | 2024-05-20 09:00:00 | 9609 Medical Center Drive, Rockville, MD, 20850 | Any | AI | Hybrid | CBIIT | 0 | Co-Clinical Imaging Research Resource Program Annual Hybrid Meeting 2024 | ||
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DescriptionAre you attending the 2024 AMIA Clinical Informatics Conference? Join NCI Fellow, Austin Fitts, as he presents on the National Childhood Cancer Registry (NCCR) during the May 22 afternoon sessions. The NCCR links cancer registry data with harmonized real-world ...Read More Are you attending the 2024 AMIA Clinical Informatics Conference? Join NCI Fellow, Austin Fitts, as he presents on the National Childhood Cancer Registry (NCCR) during the May 22 afternoon sessions. The NCCR links cancer registry data with harmonized real-world data for population-level research in childhood cancer. He will also share how NCCR’s harmonization process allows for more longitudinal studies and can serve as a model for similar data harmonization initiatives. There are future plans to publish the NCCR data model and make an initial harmonized data set available to the cancer research community through the upcoming NCCR Data Platform. Session Title: Advancing the Usability of Healthcare Data
DetailsOrganizerCBIITWhenWed, May 22, 2024 - 4:00 pm - 5:00 pmWhereOnline |
Are you attending the 2024 AMIA Clinical Informatics Conference? Join NCI Fellow, Austin Fitts, as he presents on the National Childhood Cancer Registry (NCCR) during the May 22 afternoon sessions. The NCCR links cancer registry data with harmonized real-world data for population-level research in childhood cancer. He will also share how NCCR’s harmonization process allows for more longitudinal studies and can serve as a model for similar data harmonization initiatives. There are future plans to publish the NCCR data model and make an initial harmonized data set available to the cancer research community through the upcoming NCCR Data Platform. Session Title: Advancing the Usability of Healthcare Data Austin Fitts, Pharm.D., is a post-doctoral fellow at NCI’s Surveillance Research Program. He completed his Doctor of Pharmacy degree from University of Mississippi School of Pharmacy in 2021. Dr. Fitts completed residencies in hospital pharmacy at North Mississippi Medical Center and pharmacy informatics at Vanderbilt University Medical Center. His current professional interests include pharmacy informatics, pediatric oncology, and pharmacoepidemiology. | 2024-05-22 16:00:00 | Online | Any | AI | Online | Austin Fitts (NCI’s Surveillance Research Program) | CBIIT | 0 | Harmonization of Real-World Data to Common Data Elements for the National Childhood Cancer Registry | |
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Distinguished Speakers Seminar SeriesDescriptionAn exciting opportunity at the intersection of the biomedical sciences and machine learning stems from the growing availability of large-scale multi-modal data (imaging-based and sequencing-based, observational and perturbational, at the single-cell level, tissue-level, and organism-level). Traditional representation learning methods, although often highly successful in predictive tasks, do not generally elucidate underlying causal mechanisms. Dr. Uhler will present initial ideas towards building a statistical and computational framework for causal representation learning and its applications towards ...Read More An exciting opportunity at the intersection of the biomedical sciences and machine learning stems from the growing availability of large-scale multi-modal data (imaging-based and sequencing-based, observational and perturbational, at the single-cell level, tissue-level, and organism-level). Traditional representation learning methods, although often highly successful in predictive tasks, do not generally elucidate underlying causal mechanisms. Dr. Uhler will present initial ideas towards building a statistical and computational framework for causal representation learning and its applications towards identifying novel disease biomarkers as well as inferring gene regulation in health and disease. Alternative Meeting Information: Meeting number: 2312 523 4308 Password: rgE4DbPX$65 Join by video system Dial 23125234308@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2312 523 4308Register |
An exciting opportunity at the intersection of the biomedical sciences and machine learning stems from the growing availability of large-scale multi-modal data (imaging-based and sequencing-based, observational and perturbational, at the single-cell level, tissue-level, and organism-level). Traditional representation learning methods, although often highly successful in predictive tasks, do not generally elucidate underlying causal mechanisms. Dr. Uhler will present initial ideas towards building a statistical and computational framework for causal representation learning and its applications towards identifying novel disease biomarkers as well as inferring gene regulation in health and disease. Alternative Meeting Information: Meeting number: 2312 523 4308 Password: rgE4DbPX$65 Join by video system Dial 23125234308@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2312 523 4308 | 2024-05-23 13:00:00 | Online Webinar | Any | Computational Biology,Machine Learning,Statistics | Online | Caroline Uhler Ph.D. (MIT) | BTEP | 1 | Multimodal Data Integration: From Biomarkers to Mechanisms | |
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DescriptionNCI is launching the virtual Cancer AI Conversations series featuring multiple perspectives on timely topics and themes in artificial intelligence for cancer research! Each event features short talks from 2-4 subject matter experts offering diverse views on the session topic. These talks will be followed by a moderated panel discussion. “Cancer AI Conversations” are bimonthly, 1-hour virtual events featuring timely topics related to the application ...Read More NCI is launching the virtual Cancer AI Conversations series featuring multiple perspectives on timely topics and themes in artificial intelligence for cancer research! Each event features short talks from 2-4 subject matter experts offering diverse views on the session topic. These talks will be followed by a moderated panel discussion. “Cancer AI Conversations” are bimonthly, 1-hour virtual events featuring timely topics related to the application of artificial intelligence in cancer research. Each event features short talks from 2-4 subject matter experts offering diverse perspectives on the session topic. All of the Cancer AI Conversations will be recorded and posted for future viewing. DetailsOrganizerNCIWhenTue, May 28, 2024 - 11:00 am - 12:00 pmWhereOnline |
NCI is launching the virtual Cancer AI Conversations series featuring multiple perspectives on timely topics and themes in artificial intelligence for cancer research! Each event features short talks from 2-4 subject matter experts offering diverse views on the session topic. These talks will be followed by a moderated panel discussion. “Cancer AI Conversations” are bimonthly, 1-hour virtual events featuring timely topics related to the application of artificial intelligence in cancer research. Each event features short talks from 2-4 subject matter experts offering diverse perspectives on the session topic. All of the Cancer AI Conversations will be recorded and posted for future viewing. | 2024-05-28 11:00:00 | Online | Any | Artificial Intelligence / Machine Learning | Online | Tina Hernandez-Boussard (Stanford U),Katharine Rendle (Upenn) | NCI | 0 | Cancer AI Conversations: Machine Learning in Cancer Care Delivery: Implementation and Sustainability | |
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DescriptionThis 90-minute course equips participants with essential knowledge and skills for effective interactions with Large Language Models (LLMs), such as ChatGPT. Explore the intricacies of prompt engineering and its pivotal role in optimizing the conversational capabilities of LLMs. Emphasizing best practices and practical applications, this course features live demonstrations and group discussion, and provides valuable skills for the effective use of LLMs. Attendees are encouraged to Read More This 90-minute course equips participants with essential knowledge and skills for effective interactions with Large Language Models (LLMs), such as ChatGPT. Explore the intricacies of prompt engineering and its pivotal role in optimizing the conversational capabilities of LLMs. Emphasizing best practices and practical applications, this course features live demonstrations and group discussion, and provides valuable skills for the effective use of LLMs. Attendees are encouraged to register for a free ChatGPT account prior to taking this class. DetailsOrganizerNIH LibraryWhenThu, May 30, 2024 - 12:00 pm - 1:30 pmWhereOnline |
This 90-minute course equips participants with essential knowledge and skills for effective interactions with Large Language Models (LLMs), such as ChatGPT. Explore the intricacies of prompt engineering and its pivotal role in optimizing the conversational capabilities of LLMs. Emphasizing best practices and practical applications, this course features live demonstrations and group discussion, and provides valuable skills for the effective use of LLMs. Attendees are encouraged to register for a free ChatGPT account prior to taking this class. | 2024-05-30 12:00:00 | Online | Any | AI,CHATGPT,Large language models | Online | Alicia Lillich (NIH Library),Joelle Mornini (NIH Library) | NIH Library | 0 | Best Practices and Patterns for Prompt Generation in ChatGPT | |
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Distinguished Speakers Seminar SeriesDescriptionThe Brooks Lab developed a computational tool called FLAIR (Full-Length Alternative Isoform Analysis of RNA) to produce confident transcript isoforms from long-read RNA-seq data with the aim of alternative isoform detection and quantification. With an increase in the usage of long-read RNA-seq, there is a growing need for a systematic evaluation of this approach. We are part of an international community effort called the Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) to perform such ...Read More The Brooks Lab developed a computational tool called FLAIR (Full-Length Alternative Isoform Analysis of RNA) to produce confident transcript isoforms from long-read RNA-seq data with the aim of alternative isoform detection and quantification. With an increase in the usage of long-read RNA-seq, there is a growing need for a systematic evaluation of this approach. We are part of an international community effort called the Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) to perform such an evaluation. The Brooks Lab is extending FLAIR to incorporate sequence variation, RNA editing, and RNA modification in isoform detection as well as detection of complex gene fusions from long-read sequencing data. Meeting number: 2311 656 4503 Password: ySkM7uW6B$5 Join by video system Dial 23116564503@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2311 656 4503Register |
The Brooks Lab developed a computational tool called FLAIR (Full-Length Alternative Isoform Analysis of RNA) to produce confident transcript isoforms from long-read RNA-seq data with the aim of alternative isoform detection and quantification. With an increase in the usage of long-read RNA-seq, there is a growing need for a systematic evaluation of this approach. We are part of an international community effort called the Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) to perform such an evaluation. The Brooks Lab is extending FLAIR to incorporate sequence variation, RNA editing, and RNA modification in isoform detection as well as detection of complex gene fusions from long-read sequencing data. Meeting number: 2311 656 4503 Password: ySkM7uW6B$5 Join by video system Dial 23116564503@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2311 656 4503 | 2024-06-06 13:00:00 | Online Webinar | Any | Cancer,Long-read sequencing | Online | Angela Brooks Ph.D. (UCSC) | BTEP | 1 | A More Comprehensive Landscape of RNA Alterations in Cancer with Long-read Sequencing | |
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Distinguished Speakers Seminar SeriesDescription
Dr. Irizarry will share findings demonstrating limitations of current
workflows that are popular in single cell RNA-Seq data analysis. Specifically, he will describe challenges and solutions to dimension reduction, cell-type classification, and statistical significance analysis of clustering. Dr. Irizarry will end the talk describing some of his work related to spatial transcriptomics. Specifically, he will describe approaches to cell type annotation that account for presence of multiple cell-types ...Read More
Dr. Irizarry will share findings demonstrating limitations of current
workflows that are popular in single cell RNA-Seq data analysis. Specifically, he will describe challenges and solutions to dimension reduction, cell-type classification, and statistical significance analysis of clustering. Dr. Irizarry will end the talk describing some of his work related to spatial transcriptomics. Specifically, he will describe approaches to cell type annotation that account for presence of multiple cell-types represented in the measurements, a common occurrence with technologies such as Visium and SlideSeq. He will demonstrate how this approach facilitates the discovery of spatially varying genes. Meeting link: https://cbiit.webex.com/cbiit/j.php?MTID=m9dcd9ce21f4fa6b1a8e2d998a88c2c2b Meeting number: 2317 712 9095 Password: gUKZzp3u76? Join by video system Dial 23177129095@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2317 712 9095 Register |
Dr. Irizarry will share findings demonstrating limitations of currentworkflows that are popular in single cell RNA-Seq data analysis.Specifically, he will describe challenges and solutions to dimensionreduction, cell-type classification, and statistical significanceanalysis of clustering. Dr. Irizarry will end the talk describing some of hiswork related to spatial transcriptomics. Specifically, he will describeapproaches to cell type annotation that account for presence ofmultiple cell-types represented in the measurements, a commonoccurrence with technologies such as Visium and SlideSeq. He willdemonstrate how this approach facilitates the discovery of spatiallyvarying genes. Meeting link: https://cbiit.webex.com/cbiit/j.php?MTID=m9dcd9ce21f4fa6b1a8e2d998a88c2c2b Meeting number: 2317 712 9095 Password: gUKZzp3u76? Join by video system Dial 23177129095@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2317 712 9095 | 2024-06-20 13:00:00 | Online Webinar | Any | Biomarkers,Diagnostics | Online | Rafael Irizarry Ph.D. (Harvard) | BTEP | 1 | Statistical Methods for Single-Cell RNA-Seq Analysis and Spatial Transcriptomics | |
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AI in Biomedical Research @ NIH Seminar SeriesDescriptionCARD is a collaborative initiative of the National Institute on Aging and the National Institute of Neurological Disorders and Stroke that supports basic, translational, and clinical research on Alzheimer’s disease and related dementias. CARD’s central mission is to initiate, stimulate, accelerate, and support research that will lead to the development of improved treatments and preventions for these diseases. Alternative Meeting Information: Meeting number: 2310 497 7985 Password: mjPjjmi$473 Join by video ...Read MoreCARD is a collaborative initiative of the National Institute on Aging and the National Institute of Neurological Disorders and Stroke that supports basic, translational, and clinical research on Alzheimer’s disease and related dementias. CARD’s central mission is to initiate, stimulate, accelerate, and support research that will lead to the development of improved treatments and preventions for these diseases. Alternative Meeting Information: Meeting number: 2310 497 7985 Password: mjPjjmi$473 Join by video system Dial 23104977985@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2310 497 7985Register |
CARD is a collaborative initiative of the National Institute on Aging and the National Institute of Neurological Disorders and Stroke that supports basic, translational, and clinical research on Alzheimer’s disease and related dementias. CARD’s central mission is to initiate, stimulate, accelerate, and support research that will lead to the development of improved treatments and preventions for these diseases. Alternative Meeting Information: Meeting number: 2310 497 7985 Password: mjPjjmi$473 Join by video system Dial 23104977985@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2310 497 7985 | 2024-06-27 13:00:00 | Online Webinar | Any | AI | Online | Faraz Fahri Ph.D. (CARD) | BTEP | 1 | Faraz Faghri | |
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AI in Biomedical Research @ NIH Seminar SeriesDescriptionKerry Goetz, Ph.D. Meeting number: 2302 034 0947 Password: juFCdpx$627 Join by video system Dial 23020340947@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2302 034 0947Kerry Goetz, Ph.D. Meeting number: 2302 034 0947 Password: juFCdpx$627 Join by video system Dial 23020340947@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2302 034 0947Register |
Kerry Goetz, Ph.D. Meeting number: 2302 034 0947 Password: juFCdpx$627 Join by video system Dial 23020340947@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2302 034 0947 | 2024-07-25 13:00:00 | Online Webinar | Any | AI | Online | Kerry Goetz Ph.D. (NEI) | BTEP | 1 | Kerry Goetz, Ph.D. | |
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Distinguished Speakers Seminar SeriesDescriptionThe Elemento lab combines Big Data analytics with experimentation to develop entirely new ways to help prevent, diagnose, understand, treat and ultimately cure disease. Our research involves routine use of ultrafast DNA sequencing, proteomics, high-performance computing, mathematical modeling, and artificial intelligence/machine learning. We’re revolutionizing healthcare by developing innovative approaches to better predict, diagnose, treat, and prevent disease to improve clinical care for every patient. Alternative Meeting Information: ...Read MoreThe Elemento lab combines Big Data analytics with experimentation to develop entirely new ways to help prevent, diagnose, understand, treat and ultimately cure disease. Our research involves routine use of ultrafast DNA sequencing, proteomics, high-performance computing, mathematical modeling, and artificial intelligence/machine learning. We’re revolutionizing healthcare by developing innovative approaches to better predict, diagnose, treat, and prevent disease to improve clinical care for every patient. Alternative Meeting Information: Meeting number: 2319 759 4122 Password: Join by video system Dial 23197594122@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2319 759 4122Register |
The Elemento lab combines Big Data analytics with experimentation to develop entirely new ways to help prevent, diagnose, understand, treat and ultimately cure disease. Our research involves routine use of ultrafast DNA sequencing, proteomics, high-performance computing, mathematical modeling, and artificial intelligence/machine learning. We’re revolutionizing healthcare by developing innovative approaches to better predict, diagnose, treat, and prevent disease to improve clinical care for every patient. Alternative Meeting Information: Meeting number: 2319 759 4122 Password: Join by video system Dial 23197594122@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2319 759 4122 | 2024-08-08 13:00:00 | Online | Any | AI,Precision Medicine | Online | Olivier Elemento Ph.D. (Weill Cornell Medicine) | BTEP | 1 | Genomes, Avatars and AI: The Future of Personalized Medicine | |
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Distinguished Speakers Seminar SeriesDescriptionDr. Mardis is an internationally recognized expert in cancer genomics, with ongoing interests in the integrated characterization of cancer genomes, defining DNA-based somatic and germline interactions and RNA-based pathways, and immune microenvironments that lead to cancer onset and progression, specifically involving pediatric cancers. Most recently, her research has been oriented toward translational aspects of cancer genomics, specifically identifying how the cancer genome changes with treatment, including acquired resistance, the use of genomics in understanding ...Read More Dr. Mardis is an internationally recognized expert in cancer genomics, with ongoing interests in the integrated characterization of cancer genomes, defining DNA-based somatic and germline interactions and RNA-based pathways, and immune microenvironments that lead to cancer onset and progression, specifically involving pediatric cancers. Most recently, her research has been oriented toward translational aspects of cancer genomics, specifically identifying how the cancer genome changes with treatment, including acquired resistance, the use of genomics in understanding immune therapy response, and the clinical benefit of cancer molecular profiling in the pediatric setting. Alternative Meeting Information: Meeting number: 2312 714 2024 Password: GrddnZQ*248 Join by video system Dial 23127142024@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2312 714 2024Register |
Dr. Mardis is an internationally recognized expert in cancer genomics, with ongoing interests in the integrated characterization of cancer genomes, defining DNA-based somatic and germline interactions and RNA-based pathways, and immune microenvironments that lead to cancer onset and progression, specifically involving pediatric cancers. Most recently, her research has been oriented toward translational aspects of cancer genomics, specifically identifying how the cancer genome changes with treatment, including acquired resistance, the use of genomics in understanding immune therapy response, and the clinical benefit of cancer molecular profiling in the pediatric setting. Alternative Meeting Information: Meeting number: 2312 714 2024 Password: GrddnZQ*248 Join by video system Dial 23127142024@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2312 714 2024 | 2024-08-29 13:00:00 | Online Webinar | Any | Cancer genomics,Pediatric Cancer | Online | Elaine Mardis Ph.D. (Nationwide Children\'s Hospital) | BTEP | 1 | Clinical and Computational Molecular Profiling in Pediatric Cancer Diagnostics | |
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Distinguished Speakers Seminar SeriesDescriptionDr. O'Neill's research programs employ molecular genetics, genomics and computational approaches to study the mechanisms that maintain, and disrupt, genome stability with a particular focus on repetitive elements. Projects include studying: retroelement transcription and centromere function; novel small RNA biogenesis pathways; and global chromosome and genome changes during instability (such as in cancer and hybrid dysgenesis). In addition, we use a diverse set of rapidly evolving next generation sequencing (NGS) technologies and novel library ...Read More Dr. O'Neill's research programs employ molecular genetics, genomics and computational approaches to study the mechanisms that maintain, and disrupt, genome stability with a particular focus on repetitive elements. Projects include studying: retroelement transcription and centromere function; novel small RNA biogenesis pathways; and global chromosome and genome changes during instability (such as in cancer and hybrid dysgenesis). In addition, we use a diverse set of rapidly evolving next generation sequencing (NGS) technologies and novel library preparation and computational methodologies for drafting and characterizing genome sequences in efforts to establish broad eukaryotic species as models for studying genome biology. Recently, Dr. O'Neill's lab has expanded their efforts towards applying broad NGS techniques to both model and non-model systems to understand the dynamic response of the genome to environmental queues, such as global warming. Meeting number: 2315 524 3558 Password: JEexR5Jq@63 Join by video system Dial 23155243558@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2315 524 3558Register |
Dr. O'Neill's research programs employ molecular genetics, genomics and computational approaches to study the mechanisms that maintain, and disrupt, genome stability with a particular focus on repetitive elements. Projects include studying: retroelement transcription and centromere function; novel small RNA biogenesis pathways; and global chromosome and genome changes during instability (such as in cancer and hybrid dysgenesis). In addition, we use a diverse set of rapidly evolving next generation sequencing (NGS) technologies and novel library preparation and computational methodologies for drafting and characterizing genome sequences in efforts to establish broad eukaryotic species as models for studying genome biology. Recently, Dr. O'Neill's lab has expanded their efforts towards applying broad NGS techniques to both model and non-model systems to understand the dynamic response of the genome to environmental queues, such as global warming. Meeting number: 2315 524 3558 Password: JEexR5Jq@63 Join by video system Dial 23155243558@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2315 524 3558 | 2024-09-12 13:00:00 | Online Webinar | Any | Cancer genomics,Repetive Elements | Online | Rachel O\'Neill Ph.D. (Univ. of Connecticut) | BTEP | 1 | Rachel O'Neill | |
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Distinguished Speakers Seminar SeriesDescriptionDr. Blackshaw's work examines the molecular basis of neuronal and glial cell fate specification and survival, focusing on characterizing the network of genes that control specification of different cell types within the retina and hypothalamus, two structures that arise from the embryonic forebrain. The ultimate goal is to use insights gained from learning how individual cell types are specified to understand how these cells contribute to the regulation of behavior, and how ...Read More Dr. Blackshaw's work examines the molecular basis of neuronal and glial cell fate specification and survival, focusing on characterizing the network of genes that control specification of different cell types within the retina and hypothalamus, two structures that arise from the embryonic forebrain. The ultimate goal is to use insights gained from learning how individual cell types are specified to understand how these cells contribute to the regulation of behavior, and how they can be replaced in neurodegenerative disease. Meeting number: 2312 437 6963 Password: bMrGtiA@933 Join by video system Dial 23124376963@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2312 437 6963Register |
Dr. Blackshaw's work examines the molecular basis of neuronal and glial cell fate specification and survival, focusing on characterizing the network of genes that control specification of different cell types within the retina and hypothalamus, two structures that arise from the embryonic forebrain. The ultimate goal is to use insights gained from learning how individual cell types are specified to understand how these cells contribute to the regulation of behavior, and how they can be replaced in neurodegenerative disease. Meeting number: 2312 437 6963 Password: bMrGtiA@933 Join by video system Dial 23124376963@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2312 437 6963 | 2024-11-07 13:00:00 | Online Webinar | Any | Online | Seth Blackshaw Ph.D. (Johns Hopkins) | BTEP | 1 | Building and Rebuilding the Vertebrate Retina, One Cell at a Time | ||
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AI in Biomedical Research @ NIH Seminar SeriesDescriptionDavid M. Reif, Ph.D., joined the NIEHS in 2022 as Chief of the Predictive Toxicology Branch (PTB) in the Division of Translational Toxicology (DTT). In this role, he will leverage expertise of the branch in data science, toxicogenomics, spatiotemporal exposures and toxicology, computational methods development, and new approach methods (NAMs) to advance predictive toxicology applications with partners across NIEHS, the interagency Tox21 Program and the Interagency Coordinating Committee on the Validation of Alternative Methods (...Read More David M. Reif, Ph.D., joined the NIEHS in 2022 as Chief of the Predictive Toxicology Branch (PTB) in the Division of Translational Toxicology (DTT). In this role, he will leverage expertise of the branch in data science, toxicogenomics, spatiotemporal exposures and toxicology, computational methods development, and new approach methods (NAMs) to advance predictive toxicology applications with partners across NIEHS, the interagency Tox21 Program and the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM). Meeting number: 2318 207 2771 Password: 5DMpVr5Mt5@ Join by video system Dial 23182072771@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2318 207 2771Register |
David M. Reif, Ph.D., joined the NIEHS in 2022 as Chief of the Predictive Toxicology Branch (PTB) in the Division of Translational Toxicology (DTT). In this role, he will leverage expertise of the branch in data science, toxicogenomics, spatiotemporal exposures and toxicology, computational methods development, and new approach methods (NAMs) to advance predictive toxicology applications with partners across NIEHS, the interagency Tox21 Program and the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM). Meeting number: 2318 207 2771 Password: 5DMpVr5Mt5@ Join by video system Dial 23182072771@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2318 207 2771 | 2024-11-14 13:00:00 | Online Webinar | Any | AI | Online | David Reif Ph.D. (NIEHS) | BTEP | 1 | David Reif, Ph.D. | |
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Distinguished Speakers Seminar SeriesDescriptionThe primary theme of Dr. Bult's personal research program is “bridging the digital biology divide,” reflecting the critical role that informatics and computational biology play in modern biomedical research. Dr. Bult is a Principal Investigator in the Mouse Genome Informatics (MGI) consortium that develops knowledge-bases to advance the laboratory mouse as a model system for research into the genetic and genomic basis of human biology and disease. Recent research initiatives ...Read More The primary theme of Dr. Bult's personal research program is “bridging the digital biology divide,” reflecting the critical role that informatics and computational biology play in modern biomedical research. Dr. Bult is a Principal Investigator in the Mouse Genome Informatics (MGI) consortium that develops knowledge-bases to advance the laboratory mouse as a model system for research into the genetic and genomic basis of human biology and disease. Recent research initiatives in Dr. Bult's research group include computational prediction of gene function in the mouse and the use of the mouse to understand genetic pathways in normal lung development and disease. Join information Alternative Meeting Information: Meeting number: 2309 763 3797 Password: GmUAeeZ@236 Join by video system Dial 23097633797@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2309 763 3797Register |
The primary theme of Dr. Bult's personal research program is “bridging the digital biology divide,” reflecting the critical role that informatics and computational biology play in modern biomedical research. Dr. Bult is a Principal Investigator in the Mouse Genome Informatics (MGI) consortium that develops knowledge-bases to advance the laboratory mouse as a model system for research into the genetic and genomic basis of human biology and disease. Recent research initiatives in Dr. Bult's research group include computational prediction of gene function in the mouse and the use of the mouse to understand genetic pathways in normal lung development and disease. Join information Alternative Meeting Information: Meeting number: 2309 763 3797 Password: GmUAeeZ@236 Join by video system Dial 23097633797@cbiit.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone 1-650-479-3207 Call-in number (US/Canada) Access code: 2309 763 3797 | 2024-11-21 13:00:00 | Online | Any | Cancer genomics,Mouse | Online | Carol Bult Ph.D. (The Jackson Lab) | BTEP | 1 | Pre-clinical Evaluation of Targeted Therapies for Pediatric Cancer |