Bioinformatics Training & Education Program

Virtual Office Hours where you can get hands-on help, tips, and answers as you begin using Copilot.

Join us for a quick tour of a “day in the life” with Microsoft 365 Copilot. In this 60-minute overview, see how M365 Copilot helps you manage emails, prep for meetings, and create documents effortlessly in Outlook, Teams, Word, Excel, and PowerPoint. Boost your productivity and make every day easier! Imagine starting your day with a clear inbox, joining meetings fully prepared, and creating polished documents in record time with the help of M365 Copilot. Join us to see how Copilot transforms everyday tasks into effortless productivity!

Advanced ChatGPT training is part 3 of a three-part series. 

This one-hour online training, led by OpenAI experts, is for those who have completed the ChatGPT 101 and 102 trainings. The training will focus on leveraging two of ChatGPT Enterprise's most powerful features: Custom GPTs and Data Analysis. Attendees will learn how to create specialized GPTs tailored for specific NIH tasks and how to use the Data Analysis feature to upload, interpret, and visualize data sets for deeper insights. This training is designed to provide the skills needed to apply these advanced tools to complex, enterprise-level projects. 

By the end of this training, attendees will be able to: 

• Build and deploy Custom GPTs tailored to specific NIH workflows. 
• Use the Data Analysis feature to upload, analyze, and visualize data. 
• Apply advanced techniques to solve complex problems using ChatGPT Enterprise. 

Attendees are expected to be able to utilize ChatGPT to be successful in this training.  

You can register for the other trainings in this series via the link(s) below:  

 ChatGPT 101

ChatGPT 102

Artificial Evolution with Artificial Intelligence

Virtual Office Hours where you can get hands-on help, tips, and answers as you begin using Copilot.

During this webinar, Dr. Jens Luebeck, a member of one of the winning 2022 Grand Cancer Challenges teams an Associate Project Scientist of computer science at UC San Diego, will show you how to:

• detect and classify focal amplification mechanisms (including ecDNA and breakage-fusion-bridge cycles) directly from your WGS data.
• distinguish structural subtypes of amplifications to better characterize tumor heterogeneity and potential resistance mechanisms in your samples.
• access and explore pre-computed ecDNA predictions across NCI-funded cancer data sets including The Cancer Genome Atlas (TCGA), Pan-Cancer Analysis of Whole Genomes (PCAWG), and the Cancer Cell Line Encyclopedia (CCLE).
• apply findings from more than 6,000 analyzed samples to contextualize your own results and identify oncogene co-amplification patterns relevant to your cancer type of interest.

We will demonstrate how the Frederick Research Compute Environment (FRCE) accelerates and streamlines genomic variant annotation workflows. By leveraging parallelization and high-performance resources, FRCE enables us to efficiently process and manage large-scale genomic datasets. This approach improves throughput, reproducibility, and scalability, making variant analysis pipelines more effective for large-scale datasets.

Join us for a quick tour of a “day in the life” with Microsoft 365 Copilot. In this 60-minute overview, see how M365 Copilot helps you manage emails, prep for meetings, and create documents effortlessly in Outlook, Teams, Word, Excel, and PowerPoint. Boost your productivity and make every day easier! Imagine starting your day with a clear inbox, joining meetings fully prepared, and creating polished documents in record time with the help of M365 Copilot. Join us to see how Copilot transforms everyday tasks into effortless productivity! 

The Genomic Data Commons is releasing a new Correlation Plot Tool which provides a framework for correlating GDC molecular information (mutation, CNV, gene expression) with clinical and survival data. Using quick access features, researchers can compare mutation or CNV status of a gene with a clinical variable or survival, CNV and mutation for given genes, a gene's CNV with its expression, and gene expression level with survival. The tool assists in identifying statistically meaningful correlations between genomic variants and clinical phenotypes to uncover patterns that assist in enabling diagnostic and treatment discoveries. Join us for an overview and demonstration of the GDC Correlation Plot Tool, and associated data supporting correlative analysis.

This session will introduce the Single Cell and Spatial Core (SCSC), formerly known as CCR Single Cell Analysis Facility (CCR SCAF), offering an overview of the single-cell and spatial genomics technologies available to NCI CCR investigators. We’ll highlight core resources and support for project planning, experimental design, sequencing, and downstream data analysis, with a particular focus on how these methods can advance cancer research.

Virtual Office Hours where you can get hands-on help, tips, and answers as you begin using Copilot.

This 90-minute online training led by Google experts will introduce the foundational features of Gemini for Government, tailored specifically to accelerate research and enhance productivity within NIH workflows. This training will focus on immediate, high-impact use cases that solve everyday challenges, from drafting manuscripts to communicating scientific findings more effectively. Attendees will learn how to leverage Gemini for Government's secure, AI-powered tools to streamline tasks and will get a first look at the future of research automation with agents. 

By the end of this training, attendees will be able to: 

• Utilize Gemini for Government to accelerate daily tasks, including drafting manuscript sections and analyzing meeting notes. 
• Transform a text-based research summary into a clear and effective visual concept for an infographic. 
• Perform natural language semantic searches to instantly find and synthesize information from scientific publications. 
• Describe the potential of agents to automate research workflows. 

Attendees are not expected to have any prior knowledge of the tool to be successful in this training. Gemini for Government can be accessed at: https://go.hhs.gov/gemini  

Virtual Office Hours where you can get hands-on help, tips, and answers as you begin using Copilot.

This seminar spotlights the initial data processing steps at SCSC (CCR SCAF) as well as the early quality assessment of single-cell and spatial transcriptomics data, providing insights into dataset quality before moving on to downstream filtering and quality control in Seurat or other analysis workflows.

ChatGPT 101 training is part 1 of a three-part series.  

This 90-minute online training led by OpenAI experts will cover the fundamentals of using ChatGPT Enterprise effectively in your daily NIH workflows. Attendees will learn to navigate the ChatGPT interface, implement practices for prompt writing, and utilize key features, such as working with files, search functions, and content drafting in Canvas. The training will also demonstrate real-world use cases for improving productivity and highlight security and compliance features tailored for NIH staff. 

By the end of this training, attendees will be able to:  

• Use ChatGPT Enterprise’s foundational features, including Working with documents, Search, and Canvas. 

• Apply effective prompt strategies to generate accurate, useful outputs for NIH-specific tasks. 

• Understand best practices to help ensure responsible use of generative AI tools like ChatGPT. 

Attendees are not expected to have any prior knowledge of the tool to be successful in this training. 

This 90-minute online training led by Google experts will dive into intermediate features, including agent creation and code generation, with Gemini for Government. The training will focus on hands-on applications, including building a simple agent with Agent Designer, using vibe-coding for data analysis, and leveraging NotebookLM as a personal research assistant. Attendees will also learn how to create more sophisticated, data-driven infographics to communicate their findings. 

By the end of this training, attendees will be able to:  

• Build a simple, custom agent using Agent Designer to automate a research-related task, such as monitoring new publications. 
• Generate Python scripts using natural language (vibe-coding) to clean and analyze data. 
• Utilize NotebookLM to upload source materials, ask targeted questions across documents, and organize research insights. 
• Create a data-driven infographic that transforms raw data into a compelling visual story. 

Attendees are expected to be familiar with the basic functions of Gemini to be successful in this training (gained by attending Gemini for Government 101), attending another relevant training, and/or using Gemini previously).  Gemini for Government can be accessed at: https://go.hhs.gov/gemini  

Joinpoint regression is commonly used to model trends in time-specific estimates derived from aggregate data. These methods were developed primarily for non-survey data, such as cancer registry data, under the assumption that estimates at different time points are uncorrelated or follow an autoregressive AR(1) error structure. However, directly applying existing joinpoint methods to complex survey data-for example, multistage cluster samples from the annual National Health Interview Survey-fails to account for covariance among survey estimates induced by the sample design.

To address this limitation, we extended joinpoint methods for aggregate outcomes to accommodate potentially correlated errors arising from complex survey designs. We also developed unit-level models that account for both this correlation structure and the design-based degrees of freedom required for valid inference. This presentation introduces these methods and presents results from empirical applications and simulation studies.

All problems and concerns are welcome, from scripting problems to node allocation, to strategies for a particular project, to anything that is affecting your use of the HPC systems. The meeting connection details are emailed to all Biowulf users the week of the consult.

Email staff@hpc.nih.gov for the meeting link.

This session introduces the major ecosystems for single-cell analysis (Seurat, scverse, and Bioconductor), comparing their core data objects and highlighting key learning resources. The session then transitions into a practical walkthrough of data import and the fundamentals of the Seurat object, setting the stage for hands-on analysis in the sessions ahead.

In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering several trainings that cover general concepts behind statistics and epidemiology. These trainings will help participants better understand and prepare data, interpret results and findings, design and prepare studies, and understand the results in published literature. 

This four-hour online training will provide a brief review of the principles of epidemiology, outbreak investigations, implications in public health, key concepts and terms, and commonly used statistics in epidemiology (e.g., morbidity and mortality rates; incidence and prevalence; relative risk; odds ratio; sensitivity and specificity). Time will be devoted to questions from attendees and references will be provided for in-depth self-study. 

By the end of this training, attendees will be able to:  

• Define epidemiology and its key principles
• Share the purpose and function of outbreak investigations
• Describe methods for measuring risk
• Be familiar with screening and diagnostic accuracy indices and their differences
• Describe when to use relative risks and odds ratios
• Explain differences between confounding and interaction 

Join us for a day-long symposium exploring AI approaches in biomedical sciences, with the aim of sharing effective AI implementation strategies across NIH. 

Contact Lead Organizer Ryan O’Neill, PhD (oneillrs@nih.gov) for more info.

Sign language interpreting and CART services are available upon request to participate in this event. Individualsneeding either of these services and/or other reasonable accommodations should contact Lisa Bossert (lisa.bossert@nih.gov) by May 1.

ChatGPT 102 training is part 2 of a three-part series.  

This 90-minute online training led by OpenAI experts will dive deeper into intermediate features and strategies for maximizing ChatGPT Enterprise in NIH workflows. Building on the fundamentals from ChatGPT 101, this training will focus on intermediate features including Custom GPTs, Projects, Data Analysis, coding in Canvas, and Deep Research to enable broader value creation and collaboration with ChatGPT. Attendees will also learn how to integrate ChatGPT into specialized tasks and optimize outputs for NIH-specific use cases. 

By the end of this training, attendees will be able to: 

• Create and customize GPTs and projects to serve as tailored assistants for NIH-specific initiatives and domains. 

• Utilize additional intermediate features including Data Analysis, coding in Canvas, and Deep Research, to handle complex tasks and collaborative workflows. 

• Implement best practices for integrating ChatGPT into broader NIH processes while maintaining compliance and security standards. 

Attendees are expected to be familiar with the basic functions of ChatGPT to be successful in this training (gained by attending ChatGPT 101), attending another relevant training, and/or using ChatGPT previously).  

This 90-minute online training led by Google experts is the capstone session for power users who want to push the boundaries of AI in biomedical research. This session showcases advanced agentic workflows and complex comparative analysis. The training will feature a demo on building sophisticated research assistant agents with Agent Designer and will demonstrate additional NotebookLM use cases for research. 

By the end of this training, attendees will be able to:  

• Design a complex, multi-agent system in Agent Designer capable of automating a research sub-task, such as finding and comparing experimental protocols. 
• Apply advanced NotebookLM techniques to perform complex comparative analysis on diverse scientific data sources. 
• Develop strategies for using AI to analyze a portfolio of grants and publications to identify alignment with NIH strategic priorities. 

Attendees are expected to be able to independently utilize Gemini to be successful in this training.  Gemini for Government can be accessed at: https://go.hhs.gov/gemini  

This seminar will introduce the major steps in a standard single-cell RNA-seq analysis workflow, from quality control and filtering through normalization, dimensionality reduction, and clustering. The talk will focus on the reasoning behind each step, common choices researchers face, and how these early analytical decisions shape downstream interpretation of cell populations and biological results.

Advanced ChatGPT training is part 3 of a three-part series. 

This 90-minute online training, led by OpenAI experts, is for those who have completed the ChatGPT 101 and 102 trainings. The training will focus on leveraging two of ChatGPT Enterprise's most powerful features: Custom GPTs and Data Analysis. Attendees will learn how to create specialized GPTs tailored for specific NIH tasks and how to use the Data Analysis feature to upload, interpret, and visualize data sets for deeper insights. This training is designed to provide the skills needed to apply these advanced tools to complex, enterprise-level projects. 

By the end of this training, attendees will be able to: 

• Build and deploy Custom GPTs tailored to specific NIH workflows. 

• Use the Data Analysis feature to upload, analyze, and visualize data. 

• Apply advanced techniques to solve complex problems using ChatGPT Enterprise. 

Attendees are expected to be able to utilize ChatGPT to be successful in this training. 

Qlucore Omics Explorer is a desktop-based point-and-click software with built-in machine learning capabilities. It enables RNA sequencing (bulk and single cell), proteomics and metabolomics analysis. This software is available for NCI CCR scientists upon submitting a ticket at https://service.cancer.gov/ncisp. In this demonstration-only class, Qlucore scientist will illustrate single cell RNA sequencing analysis workflow starting from data import through performing QC, visualization, clustering (tSNE, UMAP, 3D PCA) and marker-based cell type identification. Experience using or installation of this software is not required for attendance. Participation is restricted to NIH staff.

This series invites Principal Investigators, Senior Scientists, and Senior Clinicians to share cutting-edge research and developments in their fields. Each session includes a 20-30 minute presentation followed by a Q&A or journal club discussion, fostering deeper insights and scholarly exchange. Lunch is provided. Please note this event is only open to members of the NIH community.

Recent advances in large language models (LLMs) have enabled powerful AI agents for biomedical research, yet their adoption in high-stakes settings remains limited by concerns about hallucination, opacity, and reliability. In this talk, I discuss how expert-curated domain knowledge can be used to help mitigate these challenges in general-purpose LLMs. Drawing on real-world systems and case studies such as GeneAgent (Nature Methods 2025), I will highlight design principles for building AI agents that are scientifically sound, interpretable, and suitable for biomedical research and clinical applications.

This 90-minute online training led by Google experts will introduce the foundational features of Gemini for Government, tailored specifically to accelerate research and enhance productivity within NIH workflows. This training will focus on immediate, high-impact use cases that solve everyday challenges, from drafting manuscripts to communicating scientific findings more effectively. Attendees will learn how to leverage Gemini for Government's secure, AI-powered tools to streamline tasks and will get a first look at the future of research automation with agents. 

By the end of this training, attendees will be able to: 

• Utilize Gemini for Government to accelerate daily tasks, including drafting manuscript sections and analyzing meeting notes. 
• Transform a text-based research summary into a clear and effective visual concept for an infographic. 
• Perform natural language semantic searches to instantly find and synthesize information from scientific publications. 
• Describe the potential of agents to automate research workflows. 

Attendees are not expected to have any prior knowledge of the tool to be successful in this training. Gemini for Government can be accessed at: https://go.hhs.gov/gemini  

All problems and concerns are welcome, from scripting problems to node allocation, to strategies for a particular project, to anything that is affecting your use of the HPC systems. The meeting connection details are emailed to all Biowulf users the week of the consult.

Email staff@hpc.nih.gov for the meeting link.

This 90-minute online training led by Google experts will dive into intermediate features, including agent creation and code generation, with Gemini for Government. The training will focus on hands-on applications, including building a simple agent with Agent Designer, using vibe-coding for data analysis, and leveraging NotebookLM as a personal research assistant. Attendees will also learn how to create more sophisticated, data-driven infographics to communicate their findings. 

By the end of this training, attendees will be able to:  

• Build a simple, custom agent using Agent Designer to automate a research-related task, such as monitoring new publications. 
• Generate Python scripts using natural language (vibe-coding) to clean and analyze data. 
• Utilize NotebookLM to upload source materials, ask targeted questions across documents, and organize research insights. 
• Create a data-driven infographic that transforms raw data into a compelling visual story. 

Attendees are expected to be familiar with the basic functions of Gemini to be successful in this training (gained by attending Gemini for Government 101), attending another relevant training, and/or using Gemini previously).  Gemini for Government can be accessed at: https://go.hhs.gov/gemini  

Partek Flow is a point-and-click platform for building analysis workflows for Next Generation Sequences (NGS), including DNA, bulk and single-cell RNA, spatial transcriptomics, ATAC, and ChIP, helping scientists avoid the steep learning curve of code-based NGS analysis. In this demonstration-only class, Illumina scientist will illustrate how to obtain insights to regulation of gene expression from bulk RNA and ATAC sequencing data. No prior experience or access to Partek Flow is required. Attendance is limited to NIH staff.

This 90-minute online training led by Google experts is the capstone session for power users who want to push the boundaries of AI in biomedical research. This session showcases advanced agentic workflows and complex comparative analysis. The training will feature a demo on building sophisticated research assistant agents with Agent Designer and will demonstrate additional NotebookLM use cases for research. 

By the end of this training, attendees will be able to:  

• Design a complex, multi-agent system in Agent Designer capable of automating a research sub-task, such as finding and comparing experimental protocols. 
• Apply advanced NotebookLM techniques to perform complex comparative analysis on diverse scientific data sources. 
• Develop strategies for using AI to analyze a portfolio of grants and publications to identify alignment with NIH strategic priorities. 

Attendees are expected to be able to independently utilize Gemini to be successful in this training.  Gemini for Government can be accessed at: https://go.hhs.gov/gemini  

Dr. Bocks' research utilizes a synergistic "READ, LEARN, WRITE" framework that combines multi-omics profiling, deep learning, and high-throughput CRISPR screening to map, model, and program complex cellular functions. By integrating single-cell technologies to read epigenetic states with advanced neural networks to learn their regulatory circuits, he can systematically design and write new biological instructions into human cells. They successfully applied this integrated approach to optimize immunotherapy, using large-scale in vivo CRISPR screens to identify and validate gene knockouts that significantly boost the performance of CAR T cells against solid tumors.