Research Opportunities at NIGMS. Stephen Marcus, Ph.D.

Transcription

1 Research Opportunities at NIGMS Stephen Marcus, Ph.D.

2 Mission Statement of the NIGMS The National Institute of General Medical Sciences supports basic research that increases understanding of biological processes and lays the foundation for advances in disease diagnosis, treatment and prevention. The NIGMS provides leadership in training the next generation of scientists, in enhancing the diversity of the scientific workforce, and in developing research capacities throughout the country.

3 Division of Biomedical Technology, Bioinformatics, and Computational Biology The BBCB supports: The development, use and dissemination of computational tools, sophisticated quantitative approaches and unique experimental technologies to enable studies of biological, behavioral and social systems that underlie health and disease. The creation of innovative methods to store, organize, share, visualize, integrate and analyze vast quantities of biological data. Training opportunities in the quantitative and data sciences to prepare the next generation of biomedical researchers.

4 Types of Funding Fellowships (F awards): individual awards for predoctoraland postdoctoral training Career Development (K awards); individual awards for senior postdocs or junior faculty to promote mentored, targeted career development Training grants (T awards): institutional awards to support predoctoral or postdoctoral training Research grants (R awards): individual or group research awards, many types

5 Scope of Research Grant Activity Mathematical Methods and Biostatistics Research on mathematical methods related to understanding basic biological, biomedical, and biobehavioralprocesses, including pure and applied mathematics and/or statistical tools and methods. Includes theory and algorithms. Awarded grants in the following general areas: Statistical genetics; Bayesian methods; precision medicine; biomarkers; comparative effectiveness; complex systems; privacy; high dimensional data; social media data; reproducibility; machine learning; longitudinal and time to event data; model uncertainty (VVUQ); and causal inference

6 Biostatistics T32 Training Program (6) Supports predoctoraltraining in biostatisticaltheory and evolving methodologies related to basic biomedical research including, but not limited to, bioinformatics, genetics, molecular biology, cellular processes and physiology, as well as epidemiological, clinical and behavioral studies. The goal is to ensure that a workforce of biostatisticians with a deep understanding of statistical theory and new methodologies is available to assume leadership roles related to the Nation s biomedical, clinical and behavioral research needs.

7 Bioinformatics and Computational Biology T32 Training Program (12) Support predoctoraltraining in theory and biological application of information sciences (including computer science, statistics, and mathematics). The aim is to train a new class of scientist with a primary identity as a computational biologist/bioinformaticist, and whose disciplinary core draws from an emerging set of principles of how to compute, analyze and apply biological data.

8 Logistics Who should you talk to at NIH? When should you contact NIH staff? How to identify right person to contact? What to talk about?

9 Who Program Director (PD): encourages applications, makes funding recommendations, and manages scientific aspects of grants Scientific Review Officer (SRO): manages review process Grants Management Specialist (GMS): manages financial, nonscientific aspects of grant

10 When Important to recognize the Firewall between Program and Review Before you submit an application and after the Summary Statement is released you contact the PD. During the review process you contact the SRO. After award you contact either the PD or GMS.

11 How to find right contact Friends, colleagues, other researchers Acknowledgement section of manuscripts to see who funded research NIH RePORTER( searches of funded grants Center for Scientific Review ( for rosters and other information NIH websites

12 What to talk about Always best to send an first to PD with questions before phone contact Would institute be interested in topic; scope and budget appropriate; FOA requirements; application process; study section; understand reviewer comments; prospects for funding

13 For more information Stephen Marcus, Ph.D

14 Biomedical Technology, Bioinformatics and Computational Biology Research Enterprise Computational and Systems Biology New approaches, algorithms and methods for an integrative understanding of complex biological processes Mathematical and Statistical Modeling Promote research at the interface of the biological and mathematical sciences. MIDAS - Modeling of Infectious Disease Agent Study Collaborative research to model the dynamics of infectious diseases Data Sciences New shared computing algorithms and bioinformatics methods to manage, visualize and analyze complex scientific data, including standards and ontology 14

15 BBCB Partnerships Biomedical Information Science and Technology Initiative (BISTI) Promote the optimal use of computer science and technology to address problems in biology and medicine by fostering collaborations and interdisciplinary initiatives Big Data to Knowledge Initiative (BD2K) Develop new approaches, standards, methods, tools, software and competencies that will enhance the use of biomedical Big Data by supporting research, implementation and training in the data sciences Interagency Modeling and Analysis Group (IMAG) Provide an open forum for communication among government representatives for trans-agency activities that have a broad impact in science NSF/NIGMS Initiative to support research at the interface of biological and mathematical sciences NIH/DOE Partnership for stewardship of synchrotron beamlines for structural biology and other national laboratory BTRC activities 15

16 Biomedical Information Science and Technology Initiative (BISTI) Consortium of representatives from each of the NIH institutes and centers Established in May 2000 to serve as the focus of biomedical computing issues at the NIH To make optimal use of computer science and technology to address problems in biology and medicine by fostering new basic understandings, collaborations, and transdisciplinaryinitiatives between the computational and biomedical sciences. (Susan Gregurick, Director, BBCB) 16

17 New BISTI Funding Opportunities Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R01) PA and (R43/R44) PA Major themes of research include: collaborative environments and technologies data integration analysis and modeling methodologies; novel computer science and statistical approaches. This initiative aims to address biomedical research areas in biomedical computing, informatics, and big data science through the early stage development of new software, tools and related resources, as well as the fundamental research (e.g., methodologies and approaches) leading up to that development. Cross-disciplinary collaborations are strongly encouraged 17

18 New BISTI Funding Opportunities Extended Development, Hardening and Dissemination of Technologies in Biomedical Computing, Informatics and Big Data Science (R01) PA and (R41/R42) PA Major themes of research include: collaborative environments and technologies data integration analysis and modeling methodologies; novel computer science and statistical approaches. The proposed work should apply best practices and proven methods for software design, construction, and implementation to extend the applicability of existing technologies in biomedical computing, informatics and big data science to a broader biomedical research community Cross-disciplinary collaborations are strongly encouraged 18

19 BD2K: Facilitating the broad use of data Making Data Available orecommending to change the policies, practices and culture of communities with regard to data Enabling Research Use of Clinical Data Making Data Usable 1. NIH Standards Information Resource To collect, organize and make available to the public trusted, systematically organized, and curated information about data-related standards that are widely-used in biomedical research and related activities. 19

20 BD2K: Facilitating the broad use of data Making Data Usable (cont.) 2. Frameworks for Community-Based Standards Efforts: Establish a framework of policies, governance, administrative procedures, and funding to routinely support community-based standards efforts, and Use that framework to provide catalytic support for particularly opportune efforts under BD2K that are broadly relevant to biomedical research. Making data Discoverable o Development of an NIH BD2K Data Discovery Index Coordination Consortium 20

21 BD2K Funding Opportunity Announcements - Goals FOA Goals Predoctoral Training in Biomedical Big Data Science (T32) (RFA-HG ) Revisions to Add Biomedical Big Data Training to Active Institutional Training Grants (T32) (RFA-HG ) Revisions to Add Biomedical Big Data Training to Active NLM Institutional Training Grants in Biomedical Informatics (T15) (RFA-HG ) Mentored Career Development Award in Biomedical Big Data Science for Clinicians and Doctorally Prepared Scientists (K01) (RFA-HG ) NIH Big Data to Knowledge (BD2K) Initiative Research Education: Massive Open Online Course (MOOC) on Data Management for Biomedical Big Data (R25) (RFA-LM ) NIH Big Data to Knowledge (BD2K) Initiative Research Education: Open Educational Resources for Sharing, Annotating and Curating Biomedical Big Data (R25) (RFA-LM ) Courses for Skills Development in Biomedical Big Data Science (R25) (RFA-HG ) Train predoctoralstudents: to be able to develop computational and quantitative tools and methodsfor BD Train clinicians and doctorallyprepared scientists : to be able to develop computational and quantitative approaches and tools for BD Support disseminationof curriculum materials to librarians to teach participants about finding, managing and using BD Supportdevelopment of open educational resources that cover concepts, approaches, relevant use cases and requirements for sharing, annotating and curating BD Support courses and workshops on BD topics Open Educational Resources for Biomedical Big Data (R25) (RFA-HG ) Support open educational resources (OER) focused on BD NIH Big Data to Knowledge (BD2K) Enhancing Diversity in Biomedical Data Science (R25) (RFA-MD ) NIH Big Data to Knowledge (BD2K) Biomedical Data Science Training Coordination Center (U24) (RFA-ES ) Enhance diversity and build capacityin biomedical BD research education and training at less research intensive institutions by partnering with BD2K Centers Atraining coordination center to coordinate and evaluateactivities, produce an educational resource discovery index and facilitate collaborations among stakeholders