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Computational Genomics and Data Science Program

Extracting knowledge from data is a defining challenge of science.

Overview

Computational genomics has been an important area of focus for NHGRI since the beginning of the Human Genome Project. Today, however, advances in tools and techniques for data generation are rapidly increasing the amount of data available to researchers, particularly in genomics. This increase requires researchers to rely ever more heavily on computational and data science tools for the storage, management, analysis, and visualization of data. NHGRI’s commitment to computational genomics and data science is NHGRI’s commitment to computational genomics and data science is a key component of the NHGRI 2020 Strategic Vision and is in alignment with the NIH Strategic Plan for Data Science, which provides a roadmap for modernizing the NIH-funded biomedical data science ecosystem.

Read the Genomic Data Science Fact Sheet.

  • Overview

    Computational genomics has been an important area of focus for NHGRI since the beginning of the Human Genome Project. Today, however, advances in tools and techniques for data generation are rapidly increasing the amount of data available to researchers, particularly in genomics. This increase requires researchers to rely ever more heavily on computational and data science tools for the storage, management, analysis, and visualization of data. NHGRI’s commitment to computational genomics and data science is NHGRI’s commitment to computational genomics and data science is a key component of the NHGRI 2020 Strategic Vision and is in alignment with the NIH Strategic Plan for Data Science, which provides a roadmap for modernizing the NIH-funded biomedical data science ecosystem.

    Read the Genomic Data Science Fact Sheet.

NHGRI Support

The NHGRI 2020 Strategic Vision highlights the importance of bioinformatics and computational biology by stating, “all major genomics breakthroughs to date have been accompanied by the development of groundbreaking statistical and computational methods.”  Projects involving a substantial element of computational genomics or data science account for over a quarter of NHGRI’s FY2021 budget; these areas are key components of many NHGRI grants and programs.

NHGRI’s support for computational genomics and data science follows the general principles and priorities identified in the 2022 NHGRI Funding Policy. NHGRI prioritizes funding support on “approaches generalizable across diseases and biological systems of higher order organisms and approaches that inform the development and implementation of genomics in clinical care.”  Projects focusing on a single disease are less likely to be relevant to NHGRI than those generalizable across multiple diseases.

  • NHGRI Support

    The NHGRI 2020 Strategic Vision highlights the importance of bioinformatics and computational biology by stating, “all major genomics breakthroughs to date have been accompanied by the development of groundbreaking statistical and computational methods.”  Projects involving a substantial element of computational genomics or data science account for over a quarter of NHGRI’s FY2021 budget; these areas are key components of many NHGRI grants and programs.

    NHGRI’s support for computational genomics and data science follows the general principles and priorities identified in the 2022 NHGRI Funding Policy. NHGRI prioritizes funding support on “approaches generalizable across diseases and biological systems of higher order organisms and approaches that inform the development and implementation of genomics in clinical care.”  Projects focusing on a single disease are less likely to be relevant to NHGRI than those generalizable across multiple diseases.

Program Breadth

The Computational Genomics and Data Science Program (CGDS) supports the development of advanced computational approaches, innovative data analysis tools, and data resources that provide scientific utility across the extramural research programs and divisions. The CGDS program includes a number of managed grants and programs spanning many scientific topics. These grants can be categorized usefully, though neither exhaustively nor perfectly, into three categories: Genome Analysis Tools and Software Resources, Data Management Resources, and Genome Informatics Training and Workforce Development. This structure is illustrated in Figure 1. The program structure described below should be considered as a general and not exclusive framework for organizing grants into broad scientific categories of interest to NHGRI.

 

CGDS diagram

Figure 1: CGDS Program Breadth.  See text-only version.

  • Program Breadth

    The Computational Genomics and Data Science Program (CGDS) supports the development of advanced computational approaches, innovative data analysis tools, and data resources that provide scientific utility across the extramural research programs and divisions. The CGDS program includes a number of managed grants and programs spanning many scientific topics. These grants can be categorized usefully, though neither exhaustively nor perfectly, into three categories: Genome Analysis Tools and Software Resources, Data Management Resources, and Genome Informatics Training and Workforce Development. This structure is illustrated in Figure 1. The program structure described below should be considered as a general and not exclusive framework for organizing grants into broad scientific categories of interest to NHGRI.

     

    CGDS diagram

    Figure 1: CGDS Program Breadth.  See text-only version.

Genome Analysis Tools and Software Resources

The links below lead to NIH RePORTER, a database that provides information on NIH funded grants and research activities. Each link associated with a category will display the portfolio of FY2021 grants that received funding from the NHGRI Computational Genomics and Data Science Program.

Genetic variation, clinical and phenotype analysis
  • Genetic variation, clinical and phenotype analyses.
     
Data Management Resources
Genome Informatics Training and Workforce Development
  • Online resources for workforce development: Development of online resources (e.g. MOOCs), classroom courses or events for expanding and diversifying the genome informatics workforce.
     
  • Educational resources and community engagement for transitioning genome informatics to the cloud: Non-research funding for programs designed to facilitate usage of cloud computing in genomics.
     
  • Cloud computing resources for genome informatics: Infrastructure-building funding for genomic data science in cloud computing environments.
     
 
  • Genome Analysis Tools and Software Resources

    The links below lead to NIH RePORTER, a database that provides information on NIH funded grants and research activities. Each link associated with a category will display the portfolio of FY2021 grants that received funding from the NHGRI Computational Genomics and Data Science Program.

    Genetic variation, clinical and phenotype analysis
    • Genetic variation, clinical and phenotype analyses.
       
    Data Management Resources
    Genome Informatics Training and Workforce Development
    • Online resources for workforce development: Development of online resources (e.g. MOOCs), classroom courses or events for expanding and diversifying the genome informatics workforce.
       
    • Educational resources and community engagement for transitioning genome informatics to the cloud: Non-research funding for programs designed to facilitate usage of cloud computing in genomics.
       
    • Cloud computing resources for genome informatics: Infrastructure-building funding for genomic data science in cloud computing environments.
       
     

NIH Strategic Plan for Data Science

NHGRI developed a  2020 Strategic Vision  that identifies the challenges, discoveries, and opportunities that lie on the horizon for human genomics in the coming decade. As the landscape of data science is rapidly growing, new strategic plans are crucial to guide NHGRI in pushing the forefront of genomics.

See an extensive outline of the 2020 Strategic Vision.

As a result of the rapid changes in biomedical research and information technology, several pressing issues related to the data-resource ecosystem confront NIH and other components of the biomedical research community. To address these challenges, NIH released its first Strategic Plan for Data Science on June 4, 2018, to provide a roadmap for modernizing the NIH-funded biomedical data science ecosystem. In establishing this plan, NIH addresses storing data efficiently and securely; making data usable to as many people as possible (including researchers, institutions, and the public); developing a research workforce poised to capitalize on advances in data science and information technology; and setting policies for productive, efficient, secure, and ethical data use.

  • NIH Strategic Plan for Data Science

    NHGRI developed a  2020 Strategic Vision  that identifies the challenges, discoveries, and opportunities that lie on the horizon for human genomics in the coming decade. As the landscape of data science is rapidly growing, new strategic plans are crucial to guide NHGRI in pushing the forefront of genomics.

    See an extensive outline of the 2020 Strategic Vision.

    As a result of the rapid changes in biomedical research and information technology, several pressing issues related to the data-resource ecosystem confront NIH and other components of the biomedical research community. To address these challenges, NIH released its first Strategic Plan for Data Science on June 4, 2018, to provide a roadmap for modernizing the NIH-funded biomedical data science ecosystem. In establishing this plan, NIH addresses storing data efficiently and securely; making data usable to as many people as possible (including researchers, institutions, and the public); developing a research workforce poised to capitalize on advances in data science and information technology; and setting policies for productive, efficient, secure, and ethical data use.

Workshops and Meetings

Funding Opportunities

Investigators interested in submitting applications to NHGRI are encouraged to contact NHGRI program staff before submission to discuss their specific aims and their choice of Funding Opportunity Announcement (FOA). Contact information for NHGRI program staff is at the bottom of this page. 

Investigator Initiated Research in Computational Genomics and Data Science (R01, R21, and R43/R44): PAR-21-254 and PAR-21-255, invite applications for a broad range of research efforts in computational genomics, data science, statistics, and bioinformatics relevant to one or both of basic or clinical genomic science, and broadly applicable to human health and disease.

Genomic Resource Grants for Community Resource Projects (U24): PAR-20-100 is tightly focused on supporting major genomic resources, including those in informatics. Potential applicants are strongly encouraged to contact NHGRI Program Staff before developing an application.

Trans-NIH Biomedical Knowledgebase (U24): PAR-20-097 is designed to support biomedical knowledgebases. Biomedical knowledgebases under this announcement should have the primary function to extract, accumulate, organize, annotate, and link growing bodies of information related to core datasets.

Trans-NIH Biomedical Data Repository (U24): PAR-20-089 Biomedical data repositories under this announcement should have the primary function to ingest, archive, preserve, manage, distribute, and make accessible the data related to a particular system or systems.

Development and Implementation of Clinical Informatics Tools to Enhance Patients’ Use of Genomic Information (NOSI): NOT-HG-22-011 encourages applications to develop and implement patient-facing genomic-based clinical informatics tools that facilitate or enhance patient-provider electronic communication, patient tracking and registry functions, patient self-management and support, provider electronic prescribing, test tracking, referral tracking, and health care decision-making.

Parent NIH Solicitations: R01 (PA-20-185 and PA-20-183), Parent R21 (PA-20-195 and PA-20-194), and Parent K25 (PA-20-199) solicitations. These investigator-initiated grants allow researchers to target their specific area of science relevant to NHGRI’s mission (per the NHGRI Funding Policy). Other funding opportunities include PAR-21-075, which focuses on research experiences for students seeking a master’s degree. Additionally, NIH funding opportunities for Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) grants can be found at https://sbir.nih.gov/funding.

Other Relevant NIH Funding Opportunities 

NHGRI's Funding Opportunities page links to various NHGRI funding opportunities and provides instructions for signing up for NHGRI's funding opportunities email list.

The webpage of the Office of Data Science Strategy (ODSS) provides resources and links to various informatics-related funding opportunities across the NIH and other Federal agencies.

  • Funding Opportunities

    Investigators interested in submitting applications to NHGRI are encouraged to contact NHGRI program staff before submission to discuss their specific aims and their choice of Funding Opportunity Announcement (FOA). Contact information for NHGRI program staff is at the bottom of this page. 

    Investigator Initiated Research in Computational Genomics and Data Science (R01, R21, and R43/R44): PAR-21-254 and PAR-21-255, invite applications for a broad range of research efforts in computational genomics, data science, statistics, and bioinformatics relevant to one or both of basic or clinical genomic science, and broadly applicable to human health and disease.

    Genomic Resource Grants for Community Resource Projects (U24): PAR-20-100 is tightly focused on supporting major genomic resources, including those in informatics. Potential applicants are strongly encouraged to contact NHGRI Program Staff before developing an application.

    Trans-NIH Biomedical Knowledgebase (U24): PAR-20-097 is designed to support biomedical knowledgebases. Biomedical knowledgebases under this announcement should have the primary function to extract, accumulate, organize, annotate, and link growing bodies of information related to core datasets.

    Trans-NIH Biomedical Data Repository (U24): PAR-20-089 Biomedical data repositories under this announcement should have the primary function to ingest, archive, preserve, manage, distribute, and make accessible the data related to a particular system or systems.

    Development and Implementation of Clinical Informatics Tools to Enhance Patients’ Use of Genomic Information (NOSI): NOT-HG-22-011 encourages applications to develop and implement patient-facing genomic-based clinical informatics tools that facilitate or enhance patient-provider electronic communication, patient tracking and registry functions, patient self-management and support, provider electronic prescribing, test tracking, referral tracking, and health care decision-making.

    Parent NIH Solicitations: R01 (PA-20-185 and PA-20-183), Parent R21 (PA-20-195 and PA-20-194), and Parent K25 (PA-20-199) solicitations. These investigator-initiated grants allow researchers to target their specific area of science relevant to NHGRI’s mission (per the NHGRI Funding Policy). Other funding opportunities include PAR-21-075, which focuses on research experiences for students seeking a master’s degree. Additionally, NIH funding opportunities for Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) grants can be found at https://sbir.nih.gov/funding.

    Other Relevant NIH Funding Opportunities 

    NHGRI's Funding Opportunities page links to various NHGRI funding opportunities and provides instructions for signing up for NHGRI's funding opportunities email list.

    The webpage of the Office of Data Science Strategy (ODSS) provides resources and links to various informatics-related funding opportunities across the NIH and other Federal agencies.

Program Staff

Program Directors

di_Francesco
Valentina Di Francesco, M.S.
  • Chief Data Science Strategist
  • National Human Genome Research Institute
Daniel A. Gilchrist, Ph.D.
Daniel A. Gilchrist, Ph.D.
  • Program Director
  • Division of Genome Sciences
Chris Wellington, B.S.
Chris Wellington, B.S.
  • Program Director Computational Genomics and Data Science
  • Division of Genome Sciences
Ken Wiley, Jr., Ph.D.
Ken Wiley Jr, Ph.D.
  • Program Director
  • Division of Genomic Medicine
Heidi J. Sofia, Ph.D.
Heidi J. Sofia, Ph.D.
  • Program Director
  • Division of Genomic Medicine
Shurjo Sen
Shurjo K. Sen, Ph.D.
  • Program Director
  • Division of Genome Sciences
Ajay Pillai, Ph.D.
Ajay Pillai, Ph.D.
  • Program Director
  • Division of Genome Sciences

Scientific Program Analysts

Helen Thompson
Helen Thompson
  • Scientific Program Analyst
  • Division of Genome Sciences
Ana Stevens
Ana Stevens
  • Scientific Program Anaylst
  • Division of Genomic Medicine
Sean Garin
Sean Garin
  • Scientific Program Analyst
  • Division of Genome Sciences

Last updated: March 22, 2022