ncibtep@nih.gov

Bioinformatics Training and Education Program

Classes & Events

class_id details description start_date Venues learning_levels Topic Tags delivery_method presenters Organizer seminar_series class_title
1384
Description

Dear colleagues,


The Bioinformatics and Computational Biosciences Branch (BCBB) at NIAID invites you to join us for in-person hands-on workshops that will explore biovisualization techniques. Developers of UCSF ChimeraX and Cytoscape will be on campus for Virtual Reality (VR) demos and in-person hands-on workshops. These will showcase the use of ChimeraX for visualizing and analyzing 3D medical imaging scans and 3D molecular structures, and Cytoscape for network visualization. These immersive experiences ...Read More

Dear colleagues,


The Bioinformatics and Computational Biosciences Branch (BCBB) at NIAID invites you to join us for in-person hands-on workshops that will explore biovisualization techniques. Developers of UCSF ChimeraX and Cytoscape will be on campus for Virtual Reality (VR) demos and in-person hands-on workshops. These will showcase the use of ChimeraX for visualizing and analyzing 3D medical imaging scans and 3D molecular structures, and Cytoscape for network visualization. These immersive experiences will be led by the experts from the University of California San Francisco (UCSF)’s Resource for Biocomputing, Visualization, and Informatics (RBVI).


Visit our website for additional information about the workshops and our speakers. 

ALL DAY: Virtual Reality Demonstrations


•    When: 9:30 AM – 4 PM
•    Where: FAES Terrace – 1C168
•    Drop by to explore the molecular structures and medical imaging data in virtual reality with ChimeraX. Hosted by the NIAID Biovisualization Lab. 


Visualizing Atomic Models with ChimeraX


•    When: 1:00 PM – 3:00 PM
•    Where: FAES Classroom 5 - B1C210
•    This hands-on session will introduce visualizing atomic models, X-ray maps, cryoEM maps, AlphaFold models, and NMR constraints using ChimeraX 1.7. Developed by UCSF, ChimeraX is an open-source next-generation molecular visualization program. This course is suitable for anyone who is new to using the UCSF ChimeraX application. Experienced users of ChimeraX (and Chimera) may benefit from instruction on the newest features in ChimeraX. 


Visualizing and Segmenting 3D Medical Imaging Scans


•    When: 1:30 PM – 3:00 PM
•    Where: FAES Classrooms 1 & 2
•    In this tutorial, we’ll learn how to use UCSF ChimeraX to look at a variety of medical image formats. Over the past few years, ChimeraX has been increasingly integrating medical image analysis alongside its traditional use case as a molecular visualization tool. We’ll go over those advancements in our program, first by getting our bearings loading publicly accessible anonymized images from the Cancer Imaging Archive. Using that data, we’ll explore different ways to customize the look of the data in ChimeraX. Finally, we’ll use newly developed tools for visualization and segmentation including interactive segmentation in virtual reality.


Network Visualization with Cytoscape


•    When: 3:00 PM – 4:30 PM
•    Where: FAES Classroom 5 - B1C210
•    In this tutorial, we will explore the network analysis and visualization tool Cytoscape. Cytoscape is an excellent tool to create effective network figures, integrate public network and pathway sources (e.g. STRING, NDex, IntAct, Reactome, Wikipathways) with your own proteomic or transcriptomic data. During the tutorial, we'll talk about how to load data from public sources, integrate data, and some tips and tricks for visualizing your networks. This will be a hands-on tutorial, so please bring your laptop with Cytoscape 3.10.1 loaded.


To RSVP for the workshops, please fill out this form. Space in these workshops is limited so we encourage you to sign up now.  

Details
Organizer
BCBB
When
Wed, Feb 21, 2024 - 9:30 am - 4:30 pm
Where
Building 10 – Foundation for Advanced Education in the Sciences (FAES) Classrooms and Terrace
Dear colleagues, The Bioinformatics and Computational Biosciences Branch (BCBB) at NIAID invites you to join us for in-person hands-on workshops that will explore biovisualization techniques. Developers of UCSF ChimeraX and Cytoscape will be on campus for Virtual Reality (VR) demos and in-person hands-on workshops. These will showcase the use of ChimeraX for visualizing and analyzing 3D medical imaging scans and 3D molecular structures, and Cytoscape for network visualization. These immersive experiences will be led by the experts from the University of California San Francisco (UCSF)’s Resource for Biocomputing, Visualization, and Informatics (RBVI). Visit our website for additional information about the workshops and our speakers. ALL DAY: Virtual Reality Demonstrations •    When: 9:30 AM – 4 PM•    Where: FAES Terrace – 1C168•    Drop by to explore the molecular structures and medical imaging data in virtual reality with ChimeraX. Hosted by the NIAID Biovisualization Lab.  Visualizing Atomic Models with ChimeraX •    When: 1:00 PM – 3:00 PM•    Where: FAES Classroom 5 - B1C210•    This hands-on session will introduce visualizing atomic models, X-ray maps, cryoEM maps, AlphaFold models, and NMR constraints using ChimeraX 1.7. Developed by UCSF, ChimeraX is an open-source next-generation molecular visualization program. This course is suitable for anyone who is new to using the UCSF ChimeraX application. Experienced users of ChimeraX (and Chimera) may benefit from instruction on the newest features in ChimeraX.  Visualizing and Segmenting 3D Medical Imaging Scans •    When: 1:30 PM – 3:00 PM•    Where: FAES Classrooms 1 & 2•    In this tutorial, we’ll learn how to use UCSF ChimeraX to look at a variety of medical image formats. Over the past few years, ChimeraX has been increasingly integrating medical image analysis alongside its traditional use case as a molecular visualization tool. We’ll go over those advancements in our program, first by getting our bearings loading publicly accessible anonymized images from the Cancer Imaging Archive. Using that data, we’ll explore different ways to customize the look of the data in ChimeraX. Finally, we’ll use newly developed tools for visualization and segmentation including interactive segmentation in virtual reality. Network Visualization with Cytoscape •    When: 3:00 PM – 4:30 PM•    Where: FAES Classroom 5 - B1C210•    In this tutorial, we will explore the network analysis and visualization tool Cytoscape. Cytoscape is an excellent tool to create effective network figures, integrate public network and pathway sources (e.g. STRING, NDex, IntAct, Reactome, Wikipathways) with your own proteomic or transcriptomic data. During the tutorial, we'll talk about how to load data from public sources, integrate data, and some tips and tricks for visualizing your networks. This will be a hands-on tutorial, so please bring your laptop with Cytoscape 3.10.1 loaded. To RSVP for the workshops, please fill out this form. Space in these workshops is limited so we encourage you to sign up now.   2024-02-21 09:30:00 Building 10 – Foundation for Advanced Education in the Sciences (FAES) Classrooms and Terrace Any Imaging,Virtuall Reality In-Person Tom Goddard (UC San Francisco),Zach Pearson (UCSF),John \'Scooter\" Morris (UCSF) BCBB 0 EXCLUSIVE BIOVISUALIZATION WORKSHOPS AND VIRTUAL REALITY DEMOS
1383
Description

https://cap-lab.bio(link is external)

https://(link is external)qiime2.org(link is external)

The QIIME platform, including QIIME 1 and QIIME 2 (https://qiime2.org(link is external)), has been extensively applied in microbiome research, repeatedly making analyses that were once challenging or impossible into routine tasks. While QIIME began as a marker gene (e.g., 16S, ITS, ...) analysis platform, microbiome research is rapidly transitioning toward multi-omics data, introducing many new informatics challenges. With funding from NCI’s Informatics Technology for Cancer Research program (https://itcr.cancer.gov/), QIIME 2 is transitioning to become a microbiome multi-omics data science platform. 

In this talk I will introduce QIIME 2, including our current work on expanding beyond marker gene analysis, including the new QIIME 2 Shotgun Metagenomics Distribution. I will also discuss QIIME 2’s retrospective data provenance tracking system, including our recently introduced Provenance Replay functionality (https://doi.org/10.1371/journal.pcbi.1011676(link is external)), which enables you to automatically generated new code from your existing QIIME 2 results to reproduce and "replay" analyses that you or others ran. I will describe the ways that QIIME 2 can be used, including through the Galaxy graphical user interface (https://cancer.usegalaxy.org(link is external)), its command line interface, and its Python 3 API. Full support for using QIIME 2 through these different interface types ensures that using QIIME 2 will be accessible and convenient for you, regardless of your computational background. Finally, I’ll present on QIIME 2’s extensive educational and technical support resources (https://doi.org/10.1371/journal.pcbi.1009056(link is external)) so you can start learning and applying QIIME 2 to advance your work as quickly as possible.

Details
Organizer
CBIIT
When
Wed, Feb 21, 2024 - 10:00 am - 11:00 am
Where
Online
https://cap-lab.bio(link is external) https://(link is external)qiime2.org(link is external) The QIIME platform, including QIIME 1 and QIIME 2 (https://qiime2.org(link is external)), has been extensively applied in microbiome research, repeatedly making analyses that were once challenging or impossible into routine tasks. While QIIME began as a marker gene (e.g., 16S, ITS, ...) analysis platform, microbiome research is rapidly transitioning toward multi-omics data, introducing many new informatics challenges. With funding from NCI’s Informatics Technology for Cancer Research program (https://itcr.cancer.gov/), QIIME 2 is transitioning to become a microbiome multi-omics data science platform.  In this talk I will introduce QIIME 2, including our current work on expanding beyond marker gene analysis, including the new QIIME 2 Shotgun Metagenomics Distribution. I will also discuss QIIME 2’s retrospective data provenance tracking system, including our recently introduced Provenance Replay functionality (https://doi.org/10.1371/journal.pcbi.1011676(link is external)), which enables you to automatically generated new code from your existing QIIME 2 results to reproduce and "replay" analyses that you or others ran. I will describe the ways that QIIME 2 can be used, including through the Galaxy graphical user interface (https://cancer.usegalaxy.org(link is external)), its command line interface, and its Python 3 API. Full support for using QIIME 2 through these different interface types ensures that using QIIME 2 will be accessible and convenient for you, regardless of your computational background. Finally, I’ll present on QIIME 2’s extensive educational and technical support resources (https://doi.org/10.1371/journal.pcbi.1009056(link is external)) so you can start learning and applying QIIME 2 to advance your work as quickly as possible. 2024-02-21 10:00:00 Online Any Microbiome Online J. Gregory Caporaso CBIIT 0 Toward fully reproducible microbiome multi-omics bioinformatics with QIIME 2
1357
Description

Science and Technology Group: Work in Progress Seminar Series

Meeting ID: 287 867 275 591 
Passcode: wrbFXg 

Science and Technology Group: Work in Progress Seminar Series

Meeting ID: 287 867 275 591 
Passcode: wrbFXg 

Details
Organizer
Science and Technology Group (STG)
When
Wed, Feb 21, 2024 - 11:00 am - 12:00 pm
Join Meeting
Where
Online
Science and Technology Group: Work in Progress Seminar Series Meeting ID: 287 867 275 591 Passcode: wrbFXg  2024-02-21 11:00:00 Online Any Sequencing Online Bao Tran (CRTP) Science and Technology Group (STG) 0 Second-generation vs. Third-Generation Sequencing Technology: The Last Argument of Kings?
1370
Coding Club Seminar Series

Description

Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce the versioning tool GitHub (https://github.com). At the end of this class, participants will

  • Become familiar with options available for using GitHub at NCI
  • Be able to use GitHub to
    • Create coding projects 
    • Track changes in code
    • Revert to a previous version of code
    • ...Read More

Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce the versioning tool GitHub (https://github.com). At the end of this class, participants will

  • Become familiar with options available for using GitHub at NCI
  • Be able to use GitHub to
    • Create coding projects 
    • Track changes in code
    • Revert to a previous version of code
    • Collaborate with the project team

 

Installation of software is not needed to participate.

This class will be followed by one addressing versioning using Git on February 28, 2024 from 11 AM to 12 PM. See https://bioinformatics.ccr.cancer.gov/btep/classes/version-control-using-git for information and registration.

Meeting information:

Meeting link:
https://cbiit.webex.com/cbiit/j.php?MTID=meadb08ed71552393fe486073a7a7ffc5 
Meeting number:
2308 646 3414
Password:
VRjdm9A5y$4

Join by video system
Dial 23086463414@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: 2308 646 3414

Global call-in options
https://cbiit.webex.com/webappng/sites/cbiit/meeting/info/e453fc36a706405db9991abd0f97f7bb#

Register
When
Wed, Feb 21, 2024 - 11:00 am - 12:00 pm
Join Meeting
Where
Online Webinar
Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce the versioning tool GitHub (https://github.com). At the end of this class, participants will Become familiar with options available for using GitHub at NCI Be able to use GitHub to Create coding projects  Track changes in code Revert to a previous version of code Collaborate with the project team   Installation of software is not needed to participate. This class will be followed by one addressing versioning using Git on February 28, 2024 from 11 AM to 12 PM. See https://bioinformatics.ccr.cancer.gov/btep/classes/version-control-using-git for information and registration. Meeting information: Meeting link:https://cbiit.webex.com/cbiit/j.php?MTID=meadb08ed71552393fe486073a7a7ffc5 Meeting number:2308 646 3414Password:VRjdm9A5y$4 Join by video systemDial 23086463414@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: 2308 646 3414 Global call-in optionshttps://cbiit.webex.com/webappng/sites/cbiit/meeting/info/e453fc36a706405db9991abd0f97f7bb# 2024-02-21 11:00:00 Online Webinar Beginner Coding,Data Science,Version Control Coding,Data Science,Version Control Online Joe Wu (BTEP),Nadim Rizk (CBIIT) 1 Version control using Github
1399
Description

The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools requires easy access to large high-quality annotated datasets, which are both representative and diverse. The NCI Imaging Data Commons (IDC) hosts large and diverse publicly available cancer image data collections.
 
Andrey Fedorov, Ph.D., is a researcher at Brigham and Women's ...Read More

The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools requires easy access to large high-quality annotated datasets, which are both representative and diverse. The NCI Imaging Data Commons (IDC) hosts large and diverse publicly available cancer image data collections.
 
Andrey Fedorov, Ph.D., is a researcher at Brigham and Women's Hospital (BWH) and Associate Professor in Radiology at Harvard Medical School.

Details
Organizer
CBIIT
When
Wed, Feb 21, 2024 - 11:00 am - 12:00 pm
Where
Online
The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools requires easy access to large high-quality annotated datasets, which are both representative and diverse. The NCI Imaging Data Commons (IDC) hosts large and diverse publicly available cancer image data collections. Andrey Fedorov, Ph.D., is a researcher at Brigham and Women's Hospital (BWH) and Associate Professor in Radiology at Harvard Medical School. 2024-02-21 11:00:00 Online Any AI,Imaging Online Andrey Fedorov (Brigham and Women\'s Hospital) (Harward Medical School) CBIIT 0 NCI Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence
1371
Description

During this 90-minute training session, attendees will be introduced to the interface of MATLAB, develop a solid understanding of Artificial Intelligence (AI) fundamentals, and discover additional resources and support tailored for beginners.

This is an introductory-level class taught by MathWorks. No installation of MATLAB is necessary.

During this 90-minute training session, attendees will be introduced to the interface of MATLAB, develop a solid understanding of Artificial Intelligence (AI) fundamentals, and discover additional resources and support tailored for beginners.

This is an introductory-level class taught by MathWorks. No installation of MATLAB is necessary.

Details
Organizer
NIH Library
When
Thu, Feb 22, 2024 - 10:00 am - 11:30 am
Where
Online
During this 90-minute training session, attendees will be introduced to the interface of MATLAB, develop a solid understanding of Artificial Intelligence (AI) fundamentals, and discover additional resources and support tailored for beginners. This is an introductory-level class taught by MathWorks. No installation of MATLAB is necessary. 2024-02-22 10:00:00 Online Any AI,Bioinformatics Software Online Mathworks NIH Library 0 Data Science and AI: AI for Beginners with MATLAB
1382
Description

Join us for an introduction to bioinformatics resources for NCI CCR researchers. 

Featuring: 

  • NIH Bioinformatics Calendar
  • Programming Classes (R, Unix, Python)
  • Class documentation
  • Website resources
  • working on high performance compute cluster (Biowulf/Helix)
  • Next-Gen Seq Analysis tools (Partek,Qlucore, Qiagen)
  • available workflows 
  • Cloud resources for cancer research
  • NCI cores
  • <...Read More

Join us for an introduction to bioinformatics resources for NCI CCR researchers. 

Featuring: 

  • NIH Bioinformatics Calendar
  • Programming Classes (R, Unix, Python)
  • Class documentation
  • Website resources
  • working on high performance compute cluster (Biowulf/Helix)
  • Next-Gen Seq Analysis tools (Partek,Qlucore, Qiagen)
  • available workflows 
  • Cloud resources for cancer research
  • NCI cores
  • NCI and CCR specific resources
  • NIH-wide resources
Register
Organizer
BTEP
When
Thu, Feb 22, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online Webinar
Join us for an introduction to bioinformatics resources for NCI CCR researchers.  Featuring:  NIH Bioinformatics Calendar Programming Classes (R, Unix, Python) Class documentation Website resources working on high performance compute cluster (Biowulf/Helix) Next-Gen Seq Analysis tools (Partek,Qlucore, Qiagen) available workflows  Cloud resources for cancer research NCI cores NCI and CCR specific resources NIH-wide resources 2024-02-22 13:00:00 Online Webinar Any Bioinformatics,Bioinformatics Software Online Amy Stonelake (BTEP) BTEP 0 Bioinformatics Resources for NCI CCR Scientists
1397
Description

This session will cover what are containers, and why and how to use them in your Bioinformatics workflows. We will review best practices, basic commands, and useful resources. This session is geared towards beginners. 

This will be a hybrid event. 

This session will be recorded, and materials will be shared with attendees a few days after the event. For additional details and questions, please contact Natasha Pacheco Read More

This session will cover what are containers, and why and how to use them in your Bioinformatics workflows. We will review best practices, basic commands, and useful resources. This session is geared towards beginners. 

This will be a hybrid event. 

This session will be recorded, and materials will be shared with attendees a few days after the event. For additional details and questions, please contact Natasha Pacheco natasha.pacheco@nih.gov

Details
Organizer
CCR
When
Tue, Feb 27, 2024 - 12:00 pm - 1:00 pm
Where
Building 549 Executive Board Room, Frederick
This session will cover what are containers, and why and how to use them in your Bioinformatics workflows. We will review best practices, basic commands, and useful resources. This session is geared towards beginners.  This will be a hybrid event.  This session will be recorded, and materials will be shared with attendees a few days after the event. For additional details and questions, please contact Natasha Pacheco natasha.pacheco@nih.gov 2024-02-27 12:00:00 Building 549 Executive Board Room, Frederick Any Bioinformatics Hybrid Vishal Koparde (CCBR) CCR 0 Using Containers in Bioinformatics Analyses
1390
Description

In this seminar, you'll learn about the somatic variant caller named Lancet. This accurate, open-source tool leverages local assembly and joint analysis of tumor-normal, paired, high-throughput sequence data.

New York Genome Center’s Dr. Giuseppe Narzisi will provide an overview of:

  • the methodology behind the tool.
  • how it’s benchmarking against similar tools.
  • improvements in computational performance.
  • recent integrations with third ...Read More

In this seminar, you'll learn about the somatic variant caller named Lancet. This accurate, open-source tool leverages local assembly and joint analysis of tumor-normal, paired, high-throughput sequence data.

New York Genome Center’s Dr. Giuseppe Narzisi will provide an overview of:

  • the methodology behind the tool.
  • how it’s benchmarking against similar tools.
  • improvements in computational performance.
  • recent integrations with third party tools to visually inspect the somatic variants in graph space.

Dr. Narzisi will also give a historical review of alignment-based methods. He’ll highlight limitations and the need for new genome graph approaches.

Details
Organizer
CBIIT
When
Wed, Feb 28, 2024 - 10:00 am - 11:00 am
Where
Online
In this seminar, you'll learn about the somatic variant caller named Lancet. This accurate, open-source tool leverages local assembly and joint analysis of tumor-normal, paired, high-throughput sequence data. New York Genome Center’s Dr. Giuseppe Narzisi will provide an overview of: the methodology behind the tool. how it’s benchmarking against similar tools. improvements in computational performance. recent integrations with third party tools to visually inspect the somatic variants in graph space. Dr. Narzisi will also give a historical review of alignment-based methods. He’ll highlight limitations and the need for new genome graph approaches. 2024-02-28 10:00:00 Online Any Variant Analysis Online Giuseppe Narzisi (New York Genome Center) CBIIT 0 Somatic Variant Analysis and Detection Using Localized Genome Graphs
1402
Coding Club Seminar Series

Description

Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce Git (https://git-scm.com), an open-source software used to perform versioning locally and enables users to upload code to web repositories such as GitHub. At the end of this class, participants will

  • Be able to describe Git
  • Be able to use Git to
    • Create coding projects 
    • Save and track ...Read More

Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce Git (https://git-scm.com), an open-source software used to perform versioning locally and enables users to upload code to web repositories such as GitHub. At the end of this class, participants will

  • Be able to describe Git
  • Be able to use Git to
    • Create coding projects 
    • Save and track changes to code
    • Upload code to GitHub
    • Revert to/view previous versions of code
    • Perform basic collaboration tasks

 

Installation of software is not needed to participate.

Meeting information:

Meeting link:
https://cbiit.webex.com/cbiit/j.php?MTID=meadb08ed71552393fe486073a7a7ffc5 
Meeting number:
2308 646 3414
Password:
VRjdm9A5y$4

Join by video system
Dial 23086463414@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: 2308 646 3414

Global call-in options
https://cbiit.webex.com/webappng/sites/cbiit/meeting/info/e453fc36a706405db9991abd0f97f7bb#

Register
When
Wed, Feb 28, 2024 - 11:00 am - 12:00 pm
Join Meeting
Where
Online Webinar
Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce Git (https://git-scm.com), an open-source software used to perform versioning locally and enables users to upload code to web repositories such as GitHub. At the end of this class, participants will Be able to describe Git Be able to use Git to Create coding projects  Save and track changes to code Upload code to GitHub Revert to/view previous versions of code Perform basic collaboration tasks   Installation of software is not needed to participate. Meeting information: Meeting link:https://cbiit.webex.com/cbiit/j.php?MTID=meadb08ed71552393fe486073a7a7ffc5 Meeting number:2308 646 3414Password:VRjdm9A5y$4 Join by video systemDial 23086463414@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: 2308 646 3414 Global call-in optionshttps://cbiit.webex.com/webappng/sites/cbiit/meeting/info/e453fc36a706405db9991abd0f97f7bb# 2024-02-28 11:00:00 Online Webinar Beginner Code,Data Science,Version Control Data Science,Version Control,code Online Joe Wu (BTEP) 1 Version control using Git
1334
Description

This class provides an overview of the methods used to visualize the association among two or more quantitative variables. This class will focus on scatterplots, scatterplot matrix, and visualizing paired data. Upon completion of this class, participants should be able to define bivariate data, create a scatterplot using ggplot, define linear regression, and demonstrate how to perform a simple linear regression in R. You must have taken Data Visualization in R: ggplot ...Read More

This class provides an overview of the methods used to visualize the association among two or more quantitative variables. This class will focus on scatterplots, scatterplot matrix, and visualizing paired data. Upon completion of this class, participants should be able to define bivariate data, create a scatterplot using ggplot, define linear regression, and demonstrate how to perform a simple linear regression in R. You must have taken Data Visualization in R: ggplot class to be successful in this class.

Details
Organizer
NIH Library
When
Thu, Feb 29, 2024 - 1:00 pm - 2:30 pm
Where
Online
This class provides an overview of the methods used to visualize the association among two or more quantitative variables. This class will focus on scatterplots, scatterplot matrix, and visualizing paired data. Upon completion of this class, participants should be able to define bivariate data, create a scatterplot using ggplot, define linear regression, and demonstrate how to perform a simple linear regression in R. You must have taken Data Visualization in R: ggplot class to be successful in this class. 2024-02-29 13:00:00 Online Any Programming and data visualization Online Doug Joubert (NIH Library) NIH Library 0 Data Visualization in ggplot: Visualizing Relationships and Linear Regression
1379
AI in Biomedical Research @ NIH Seminar Series

Description

Artificial Intelligence (AI) is becoming increasingly ubiquitous in biomedical research, enabled by large datasets, new algorithms, and hardware improvements. In this session, Dr. Brian Ondov will introduce the basic principles of AI and describe how its various forms can help researchers in different ways, including image classification, sequence-based prediction, generative models, and language understanding. 

 

Artificial Intelligence (AI) is becoming increasingly ubiquitous in biomedical research, enabled by large datasets, new algorithms, and hardware improvements. In this session, Dr. Brian Ondov will introduce the basic principles of AI and describe how its various forms can help researchers in different ways, including image classification, sequence-based prediction, generative models, and language understanding. 

 

Register
Organizer
BTEP
When
Thu, Feb 29, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online Webinar
Artificial Intelligence (AI) is becoming increasingly ubiquitous in biomedical research, enabled by large datasets, new algorithms, and hardware improvements. In this session, Dr. Brian Ondov will introduce the basic principles of AI and describe how its various forms can help researchers in different ways, including image classification, sequence-based prediction, generative models, and language understanding.    2024-02-29 13:00:00 Online Webinar Any AI,Biomedical Research Online Brian Ondov Ph.D. (NLM) BTEP 1 Artificial Intelligence in the Biomedical Sciences
1373
Description

This in-person workshop will show participants how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be used to illustrate a basic Single Cell RNA-Seq analysis pipeline. Partek Flow is a web-based application for the analysis of next generation sequencing (NGS) including RNA, small RNA, and DNA sequencing. With an easy-to-use graphical interface and the ability to build custom analysis pipelines, Partek Flow enables ...Read More

This in-person workshop will show participants how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be used to illustrate a basic Single Cell RNA-Seq analysis pipeline. Partek Flow is a web-based application for the analysis of next generation sequencing (NGS) including RNA, small RNA, and DNA sequencing. With an easy-to-use graphical interface and the ability to build custom analysis pipelines, Partek Flow enables users to carry out routine NGS data analysis using dozens of popular algorithms without writing codes or running command lines tools.  Attendees will need to have taken the Partek Flow Basic Components class before registering or be comfortable with Partek Flow.

By the end of this class, attendees will be able to demonstrate how to access Partek Flow from the NIH Library, discuss the Quality Control (QC) and Quality Assurance (QA) tools, identify pre- and post-alignment tools, describe options for quantification and normalization, and perform pathway analysis and visualization.

Note on Technology
Participants are expected to bring their own laptops to this training. NIH Staff using an NIH-laptop can easily connect to the staff Wi-Fi. If participants are bringing a personal laptop, they are restricted to using the NIH Public Wi-Fi. 

Registrants will receive an email with information and instructions to install and verify access to Partek Flow 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.

 

Details
Organizer
NIH Library
When
Tue, Mar 05, 2024 - 10:00 am - 12:00 pm
Where
NIH Library Training Room, Building 10, Clinical Center, South Entrance
This in-person workshop will show participants how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be used to illustrate a basic Single Cell RNA-Seq analysis pipeline. Partek Flow is a web-based application for the analysis of next generation sequencing (NGS) including RNA, small RNA, and DNA sequencing. With an easy-to-use graphical interface and the ability to build custom analysis pipelines, Partek Flow enables users to carry out routine NGS data analysis using dozens of popular algorithms without writing codes or running command lines tools.  Attendees will need to have taken the Partek Flow Basic Components class before registering or be comfortable with Partek Flow. By the end of this class, attendees will be able to demonstrate how to access Partek Flow from the NIH Library, discuss the Quality Control (QC) and Quality Assurance (QA) tools, identify pre- and post-alignment tools, describe options for quantification and normalization, and perform pathway analysis and visualization. Note on TechnologyParticipants are expected to bring their own laptops to this training. NIH Staff using an NIH-laptop can easily connect to the staff Wi-Fi. If participants are bringing a personal laptop, they are restricted to using the NIH Public Wi-Fi.  Registrants will receive an email with information and instructions to install and verify access to Partek Flow 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.   2024-03-05 10:00:00 NIH Library Training Room, Building 10, Clinical Center, South Entrance Any Single Cell RNA-Seq In-Person Partek NIH Library 0 NIH Library Workshop: Single Cell RNA-Seq Analysis & Visualization in Partek Flow
1396
Description

This in-person, hands-on training will introduce participants to single cell RNA sequencing analysis using Partek Flow, a point-and-click software for analyzing high dimensional multi-omics sequencing data. At NIH, Partek Flow is hosted on the Biowulf high performance computing cluster (HPC). Researchers interact with the software through a web browser using a URL supplied by Biowulf. This enables investigators to take advantage of the compute power offered by HPC while using a graphical user interface ...Read More

This in-person, hands-on training will introduce participants to single cell RNA sequencing analysis using Partek Flow, a point-and-click software for analyzing high dimensional multi-omics sequencing data. At NIH, Partek Flow is hosted on the Biowulf high performance computing cluster (HPC). Researchers interact with the software through a web browser using a URL supplied by Biowulf. This enables investigators to take advantage of the compute power offered by HPC while using a graphical user interface to construct a sequencing data analysis workflow. At the end of this class, participants will know how to import single cell data to their projects and perform cell type classification, obtain differentially expressed genes, identify molecular pathways as well as create visualizations such as PCA, UMAP, and t-SNE. Skills learn in this class can be applied to analysis of other high throughput sequencing types using Partek Flow. Partek will provide temporary/training access to Partek Flow, so bring a laptop to follow along!

NOTE: This is an in-person class only and takes place in NIH Building 35 (John Edward Porter Neuroscience Research Center) Room 620/630. There is no option to attend virtually, and this class will not be recorded.

Register
Organizer
BTEP
When
Tue, Mar 05, 2024 - 2:00 pm - 4:00 pm
Where
NIH Building 35 Room 620/630
This in-person, hands-on training will introduce participants to single cell RNA sequencing analysis using Partek Flow, a point-and-click software for analyzing high dimensional multi-omics sequencing data. At NIH, Partek Flow is hosted on the Biowulf high performance computing cluster (HPC). Researchers interact with the software through a web browser using a URL supplied by Biowulf. This enables investigators to take advantage of the compute power offered by HPC while using a graphical user interface to construct a sequencing data analysis workflow. At the end of this class, participants will know how to import single cell data to their projects and perform cell type classification, obtain differentially expressed genes, identify molecular pathways as well as create visualizations such as PCA, UMAP, and t-SNE. Skills learn in this class can be applied to analysis of other high throughput sequencing types using Partek Flow. Partek will provide temporary/training access to Partek Flow, so bring a laptop to follow along! NOTE: This is an in-person class only and takes place in NIH Building 35 (John Edward Porter Neuroscience Research Center) Room 620/630. There is no option to attend virtually, and this class will not be recorded. 2024-03-05 14:00:00 NIH Building 35 Room 620/630 Any Bioinformatics,Bioinformatics Software,Single Cell RNA-Seq Bioinformatics,Bioinformatics Software,Single Cell RNA-seq In-Person Joe Wu (BTEP),Xiaowen Wang (Partek) BTEP 0 Single cell RNA sequencing analysis with Partek Flow: in-person training
1398
Description

The NCI Cancer Diagnosis Program in the Division of Cancer Treatment and Diagnosis is hosting a workshop, “Digital Pathology Imaging (DPI) in Cancer Clinical Trials and Research.” This workshop will focus on the expanding role of DPI in translational cancer research, biomarker studies, clinical trials, and pharmaceutical development. The primary objectives are to understand the specific needs of investigators and biospecimen banks for DPI and to successfully integrate DPI into cancer clinical ...Read More

The NCI Cancer Diagnosis Program in the Division of Cancer Treatment and Diagnosis is hosting a workshop, “Digital Pathology Imaging (DPI) in Cancer Clinical Trials and Research.” This workshop will focus on the expanding role of DPI in translational cancer research, biomarker studies, clinical trials, and pharmaceutical development. The primary objectives are to understand the specific needs of investigators and biospecimen banks for DPI and to successfully integrate DPI into cancer clinical trials. Workshop speakers will present the challenges of digital and computational pathology, including diverse hardware and software, image acquisition, validation, storage, data management, intellectual property, and public-private partnerships. The meeting will gather members of the scientific community, leaders of cancer clinical trials, representatives from NCI biospecimen banks, pathologists, radiologists, IT scientists, and policy advisors. The workshop participants will discuss how to best address challenges posed by the current lack of standardized approaches for DPI utilization in clinical trials and biobanking and will propose potential solutions.

See the agenda and speaker information on the event page

 

 

Details
Organizer
NCI
When
Wed, Mar 06 - Thu, Mar 07, 2024 -9:00 am - 5:00 pm
Where
Online
The NCI Cancer Diagnosis Program in the Division of Cancer Treatment and Diagnosis is hosting a workshop, “Digital Pathology Imaging (DPI) in Cancer Clinical Trials and Research.” This workshop will focus on the expanding role of DPI in translational cancer research, biomarker studies, clinical trials, and pharmaceutical development. The primary objectives are to understand the specific needs of investigators and biospecimen banks for DPI and to successfully integrate DPI into cancer clinical trials. Workshop speakers will present the challenges of digital and computational pathology, including diverse hardware and software, image acquisition, validation, storage, data management, intellectual property, and public-private partnerships. The meeting will gather members of the scientific community, leaders of cancer clinical trials, representatives from NCI biospecimen banks, pathologists, radiologists, IT scientists, and policy advisors. The workshop participants will discuss how to best address challenges posed by the current lack of standardized approaches for DPI utilization in clinical trials and biobanking and will propose potential solutions. See the agenda and speaker information on the event page     2024-03-06 09:00:00 Online Any Imaging Online NCI 0 NCI/DCTD/CDP Virtual Workshop on Digital Pathology Imaging in Cancer Clinical Trials and Research
1375
Description

This one-hour training will provide detailed information on how to create charts in MS Excel, including reviewing and selecting chart types, layouts, and styles. The training will also cover changing colors and format options, as well as how to make changes to titles and labels. This is an introductory class for those who need to quickly learn basic Excel chart features and for those who are interested in a ...Read More

This one-hour training will provide detailed information on how to create charts in MS Excel, including reviewing and selecting chart types, layouts, and styles. The training will also cover changing colors and format options, as well as how to make changes to titles and labels. This is an introductory class for those who need to quickly learn basic Excel chart features and for those who are interested in a refresher.  

No previous experience with Excel is required, but basic familiarity with Microsoft Office is helpful. 

Details
Organizer
NIH Library
When
Thu, Mar 07, 2024 - 12:00 pm - 1:00 pm
Where
Online
This one-hour training will provide detailed information on how to create charts in MS Excel, including reviewing and selecting chart types, layouts, and styles. The training will also cover changing colors and format options, as well as how to make changes to titles and labels. This is an introductory class for those who need to quickly learn basic Excel chart features and for those who are interested in a refresher.   No previous experience with Excel is required, but basic familiarity with Microsoft Office is helpful.  2024-03-07 12:00:00 Online Any Data Visualization Online Raisa Ionin (NIH Library) NIH Library 0 Creating Charts in Excel
1376
Description

In this webinar, the participants will learn about application of machine learning methods, specifically geared towards predicting the toxicity of target molecules. They will gain insights into various machine learning techniques, fostering a comprehensive understanding of their application in this critical domain. Furthermore, attendees will acquire the skills to apply machine learning to their data, utilize applications to train artificial intelligence (AI) models for toxicity prediction, and effortlessly share the results with collaborators.

<...Read More

In this webinar, the participants will learn about application of machine learning methods, specifically geared towards predicting the toxicity of target molecules. They will gain insights into various machine learning techniques, fostering a comprehensive understanding of their application in this critical domain. Furthermore, attendees will acquire the skills to apply machine learning to their data, utilize applications to train artificial intelligence (AI) models for toxicity prediction, and effortlessly share the results with collaborators.

This is an introductory level class taught by MathWorks. No installation of MATLAB is necessary. 

Details
Organizer
NIH Library
When
Tue, Mar 12, 2024 - 12:00 pm - 1:00 pm
Where
Online
In this webinar, the participants will learn about application of machine learning methods, specifically geared towards predicting the toxicity of target molecules. They will gain insights into various machine learning techniques, fostering a comprehensive understanding of their application in this critical domain. Furthermore, attendees will acquire the skills to apply machine learning to their data, utilize applications to train artificial intelligence (AI) models for toxicity prediction, and effortlessly share the results with collaborators. This is an introductory level class taught by MathWorks. No installation of MATLAB is necessary.  2024-03-12 12:00:00 Online Any AI Online Mathworks NIH Library 0 Data Science and AI: Predicting Toxicity in Small Molecules using MATLAB
1377
Description

Electronic lab notebooks (ELNs) are digital tools that allow researchers to record, manage, and share their data and results in a secure and efficient way. The virtual roundtable discussion will cover various aspects of using ELNs in biomedical research, such as general best practices and use cases; specific considerations for technology transfer, records management, and pre-clinical studies; and avoiding scientific misconduct. The participants will learn from the presentations of experts and practitioners with experience ...Read More

Electronic lab notebooks (ELNs) are digital tools that allow researchers to record, manage, and share their data and results in a secure and efficient way. The virtual roundtable discussion will cover various aspects of using ELNs in biomedical research, such as general best practices and use cases; specific considerations for technology transfer, records management, and pre-clinical studies; and avoiding scientific misconduct. The participants will learn from the presentations of experts and practitioners with experience and knowledge of different ELN platforms and solutions.

A full schedule and list of presentations and speakers will be added closer to the event date.

Details
Organizer
NIH Library
When
Mon, Mar 18, 2024 - 1:00 pm - 2:30 pm
Where
Online
Electronic lab notebooks (ELNs) are digital tools that allow researchers to record, manage, and share their data and results in a secure and efficient way. The virtual roundtable discussion will cover various aspects of using ELNs in biomedical research, such as general best practices and use cases; specific considerations for technology transfer, records management, and pre-clinical studies; and avoiding scientific misconduct. The participants will learn from the presentations of experts and practitioners with experience and knowledge of different ELN platforms and solutions. A full schedule and list of presentations and speakers will be added closer to the event date. 2024-03-18 13:00:00 Online Any Electronic Lab Notebooks (ELN) Online Alicia Lillich (NIH Library) NIH Library 0 Electronic Lab Notebooks: A Roundtable Discussion
1400
Description

The next session of Containers and Workflow Interest Group (CWIG) webinar series will be on March 20, 2024 11am-12PM ET.

Meeting number (access code): 2303 344 1474
Meeting password: 2K9AfEmfN@2

 

 

The next session of Containers and Workflow Interest Group (CWIG) webinar series will be on March 20, 2024 11am-12PM ET.

Meeting number (access code): 2303 344 1474
Meeting password: 2K9AfEmfN@2

 

 

Details
Organizer
Containers and Workflow Interest Group (CWIG)
When
Wed, Mar 20, 2024 - 11:00 am - 12:00 pm
Where
Online
The next session of Containers and Workflow Interest Group (CWIG) webinar series will be on March 20, 2024 11am-12PM ET. Meeting number (access code): 2303 344 1474Meeting password: 2K9AfEmfN@2     2024-03-20 11:00:00 Online Any Cloud,Containers Online Krish Seshadri (NCI/CBIIT/DSSB) Lawrence Brem (NCI/CBIIT) Containers and Workflow Interest Group (CWIG) 0 Use of Containers for Custom Software Development at the NCI for AWS Cloud and On Premises
1355
Description

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 ...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.

Details
Organizer
NCI
When
Tue, Mar 26, 2024 - 11:00 am - 12:00 pm
Where
Online Webinar
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. 2024-03-26 11:00:00 Online Webinar Any Artificial Intelligence / Machine Learning Online Dana Farber (Cancer Center),Julian Hong (UC San Francisco),William Lotter NCI 0 Cancer AI Conversations: Machine Learning in Cancer Care Delivery: Implementation and Sustainability
1380
AI in Biomedical Research @ NIH Seminar Series

Description

Explainable Artificial Intelligence (XAI) and Single Cell Genomics to Understand the Cellular Complexity of the Human Brain

Explainable Artificial Intelligence (XAI) and Single Cell Genomics to Understand the Cellular Complexity of the Human Brain

Register
Organizer
BTEP
When
Thu, Apr 04, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online Webinar
Explainable Artificial Intelligence (XAI) and Single Cell Genomics to Understand the Cellular Complexity of the Human Brain 2024-04-04 13:00:00 Online Webinar Any AI Online Richard Scheuermann Ph.D. (NLM) BTEP 1 Explainable Artificial Intelligence (XAI) and Single Cell Genomics to Understand the Cellular Complexity of the Human Brain
1385
Distinguished Speakers Seminar Series

Description

Dr. Greene's lab develops computational methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. This approach reveals underlying principles of an organism’s genetics, its environment, and its response to that environment. Extracting this key contextual information reveals where the data’s context doesn’t fit existing models and raises the questions that a complete collection of publicly available data indicates researchers ...Read More

Dr. Greene's lab develops computational methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. This approach reveals underlying principles of an organism’s genetics, its environment, and its response to that environment. Extracting this key contextual information reveals where the data’s context doesn’t fit existing models and raises the questions that a complete collection of publicly available data indicates researchers should be asking. In addition to developing deep learning methods for extracting context, a core mission of Dr. Greene's lab is bringing these capabilities into every molecular biology lab.

Register
Organizer
BTEP
When
Thu, Apr 11, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online
Dr. Greene's lab develops computational methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. This approach reveals underlying principles of an organism’s genetics, its environment, and its response to that environment. Extracting this key contextual information reveals where the data’s context doesn’t fit existing models and raises the questions that a complete collection of publicly available data indicates researchers should be asking. In addition to developing deep learning methods for extracting context, a core mission of Dr. Greene's lab is bringing these capabilities into every molecular biology lab. 2024-04-11 13:00:00 Online Any Data Mining Online Casey Greene Ph.D. (CU Anschutz) BTEP 1 Casey Greene
1381
AI in Biomedical Research @ NIH Seminar Series

Description

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 delves into the convergence of AI and ChatGPT, highlighting their pivotal roles in revolutionizing biomedical discovery, patient care, diagnosis, treatment, and medical research. By demonstrating ...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 delves into the convergence 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 PubMed searches (Fiorini et al., Nature Biotechnology 2018), supporting precision medicine (Allot et al., Nature Genetics 2023), and assisting patient trial matching, we underscore the potential of AI and ChatGPT in enhancing clinical decision-making, personalizing patient experiences, and accelerating knowledge discovery.

Register
Organizer
BTEP
When
Thu, May 02, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online Webinar
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 delves into the convergence 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 PubMed searches (Fiorini et al., Nature Biotechnology 2018), supporting precision medicine (Allot et al., Nature Genetics 2023), and assisting patient trial matching, we underscore the potential of AI and ChatGPT in enhancing clinical decision-making, personalizing patient experiences, and accelerating knowledge discovery. 2024-05-02 13:00:00 Online Webinar Any AI,Text Mining Online Dr. Zhiyong Lu (NCBI) BTEP 1 The Future of Healthcare: How AI and ChatGPT are Changing the Game in Medicine
1401
Distinguished Speakers Seminar Series

Description

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 ...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.

Register
Organizer
BTEP
When
Thu, May 23, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online Webinar
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. 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
1356
Description

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 ...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.

Details
Organizer
NCI
When
Tue, May 28, 2024 - 11:00 am - 12:00 pm
Where
Online
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
1395
AI in Biomedical Research @ NIH Seminar Series

Description

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.

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.

Register
Organizer
BTEP
When
Thu, Jun 27, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online Webinar
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. 2024-06-27 13:00:00 Online Webinar Any AI Online Faraz Fahri Ph.D. (CARD) BTEP 1 Faraz Faghri
1391
Distinguished Speakers Seminar Series

Description

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.  

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.  

Register
Organizer
BTEP
When
Thu, Aug 08, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online
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.   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
1394
Distinguished Speakers Seminar Series

Description

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 ...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.

Register
Organizer
BTEP
When
Thu, Aug 29, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online Webinar
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. 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
1387
Distinguished Speakers Seminar Series

Description

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 ...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.

Register
Organizer
BTEP
When
Thu, Nov 07, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online Webinar
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. 2024-11-07 13:00:00 Online Webinar Any Online Seth Blackshaw Ph.D. (Johns Hopkins) BTEP 1 Seth Blackshaw
1386
Distinguished Speakers Seminar Series

Description

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. ...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.

Register
Organizer
BTEP
When
Thu, Nov 21, 2024 - 1:00 pm - 2:00 pm
Join Meeting
Where
Online
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. 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