Research Funding

Funding Opportunity Announcements

Browse below for Data Science Funding Opportunity Announcements.

This page last reviewed on September 14, 2018

Feed last updated: April 24 2019 2:15 pm
Title FOA Number Organization Release Date Expiration Date Purpose Search Terms
Request for Information (RFI) on Science Drivers Requiring Capable Exascale High Performance Computing

NOT-GM-15-122

NIGMS

Sep 15 2015

N/A

Request Information RFI) Science Drivers Requiring Capable Exascale High Performance Computing Notice Number: NOT-GM-15-122 Key Dates Release Date:   September 15, 2015 Related Announcements NOT-GM-15-123 Issued National Institute General Medical Sciences NIGMS) Purpose is multi-agency request information identify scientific research topics applications need High Performance Computing HPC) capabilities extend 100 times beyond today’s performance scientific applications. Currently, computational modeling, simulation, well data assimilation data analytics used an increasing number researchers answer complex multispatial, multiphysics scientific questions more realism. the scientific discovery horizon expands as advances high performance computing become central scientific workflows, sustained petascale application performance be insufficient meet needs. addition, HPC expanding traditional numerically oriented computation also include large-scale analytics e.g., Bayesian approaches model refinement, large-scale image analysis, machine learning, decision support, quantifying uncertainty multimodal multi spatial analyses). Architectures technologies used modeling simulation currently differ those used data integration analytics, are increasingly converging. extreme computing ecosystem must therefore accommodate broad spectrum growing data science activities. Background White House Executive Order, July 29, 2015, establishes National Strategic Computing Initiative NSCI) a whole-of-government effort designed create cohesive, multi-agency strategic vision Federal investment strategy, executed collaboration industry academia, maximize benefits HPC the United States. Department Energy DOE), National Science Foundation NSF), the Department Defense DOD) the lead agencies this effort support significantly advanced HPC ecosystem within next decade.   of objectives the initiative to deliver capable Exascale” computing capability delivers 100 times today's application performance. is request information NSF, DOE, NIH community input identifying scientific research would benefit a greatly enhanced new generation HPC far beyond can done using current technologies architectures. information be used assist agencies construct roadmap, build exascale-capable ecosystem required support scientific research, inform research, engineering development process. is likely a range advanced capabilities need be developed respond the varied computing needs across science disciplines. seek responses applications subfields life e.g., biological, social, health biomedical) sciences, mathematical physical sciences, geosciences, energy science, engineering research.  seek only traditional areas numerical intensity such simulations nuclear physics, biomolecular physics, weather climate modeling, materials science, also any areas rely deriving fundamental understanding large scale analytics would require 100-fold increase over today’s application performance. Information Requested respect your field expertise traditional non-traditional research areas applications HPC, agencies request input/feedback. comments include are limited the following areas concern: specific scientific research challenges would need projected 100-fold increase application performance over is possible today.  potential impact the research the scientific community, national economy, society.   specific limitations/barriers existing HPC systems must overcome perform studies this area.  comment also include level performance current architectures, the projected increase performance is needed future architectures. Any related research areas foresee would benefit this level augmented computational capability. Identification any barriers addition computational capability impact proposed research also considered. Important computational technical parameters the problem you expect to in 10 years 2025).  addition any specialized unique computational capabilities are required and/or need be scaled for addressing scientific problem, e.g., the areas computing architectures, systems software hardware, software applications, algorithm development, communications, networking. Alternative models deployment resource accessibility arising of exascale computing. Improvements scientific workflow well particular requirements may needed specific domains. Capabilities needed the end-to-end system, including data requirements such data analytics visualization tools, shared data capabilities, data services includes databases, portals data transfer tools/nodes. Foundational issues need be addressed such training, workforce development collaborative environments. areas relevance the Agencies consider. Submitting Response responses must submitted NIGMS_exascale@nigms.nih.gov October 16, 2015. comments must submitted via E-mail text as attached electronic document.  Microsoft documents preferred.   Please try limit response two pages total. RFI for planning purposes only should be construed a solicitation applications an obligation the part the government. government not pay the preparation any information submitted for government’s of information. agencies use information submitted response this RFI their discretion will provide comments any responder's submission. Responses the RFI be reflected future funding opportunity announcements. information provided be analyzed, appear reports, may shared publicly agency websites. Respondents advised the government under obligation acknowledge receipt the information provide feedback respondents respect any information submitted. proprietary, classified, confidential, sensitive information should included your response. government reserves right use any non-proprietary technical information any resultant solicitation(s), policies procedures. Inquiries Please direct inquiries to: Susan Gregurick, Ph.D. National Institute General Medical Sciences NIGMS) National Institutes Health Telephone: 301-451-6446 Email: susan.gregurick@nigms.nih.gov William L. Miller, Ph.D. Division Advanced Cyberinfrastructure Directorate Computer Information Science Engineering National Science Foundation Telephone: 703-292-7886 Email: WLMiller@nsf.gov Barbara Helland Advanced Scientific Computing Research ASCR) Department Energy Telephone: 301-903-9958 Email: barbara.helland@science.doe.gov

data science, computational, data integration, machine learning
Rare Disease Cohorts in Heart, Lung, Blood and Sleep Disorders (UG3/UH3 Clinical Trial Not Allowed)

RFA-HL-20-014

NHLBI

Apr 04 2019

Jun 18 2020

The purpose of this FOA is to fund research centers that will establish longitudinal cohorts in rare HLBS diseases to investigate unaddressed research questions using epidemiologic study designs and methods that are appropriate for conditions affecting fewer than 200,000 persons in the US. These observational cohort studies should be designed to provide an evidence base for future interventional studies, including clinical trials; for developing better diagnostics than those that are currently available; for answering early translational questions; or for broader implementation of guidelines for managing these diseases.
This program will provide opportunities to advance rare disease research using genetics and deep phenotyping to characterize the disease and to identify disease sub-types; to use data science methods that integrate clinical and patient-reported outcomes (PROs) with laboratory, imaging, environmental and -omics data to understand the natural history of disease; to generate data that differentiate patients with the same morphological phenotype but different genetic mutations and severity of outcomes; to elucidate genotype-phenotype interactions and multisystem phenotyping to develop reliable and valid predictive tools to determine who will respond to which treatments and when to intervene; and to encourage innovative methods such as telemedicine to include participants with rare diseases located in remote locations.
This initiative will allow applicants to study related rare diseases, disorders, conditions or syndromes together based on pathogenesis, affected biochemical, cellular or physiological features or organ system involvement. Studying related rare diseases within the same cohort could help understand the nuances, and knowledge gained from one disease and could accelerate the advances in related diseases. For example, investigators may propose to study hemoglobin disorders rather than only sickle cell anemia or thalassemia.

data science, big data, computational, informatics, common data
Pilot Services Research Grants Not Involving Clinical Trials (R34 Clinical Trial Not Allowed)

PAR-19-189

NIMH

Feb 21 2019

Jan 08 2022

The purpose of this funding announcement is to encourage pilot research that is not an immediate precursor to testing a service intervention but is consistent with NIMH priorities for services research. While NIMH now requires use of an experimental therapeutics model for all intervention studies, there is recognition that some mission-relevant areas of services research do not involve clinical trials.

data science, big data, data integration, common data
Notice to Specify High-Priority Research Topic for PAR-19-070 and PAR-19-071

NOT-AG-18-053

NIA

Dec 17 2018

N/A

Notice Specify High-Priority Research Topic PAR-19-070 PAR-19-071 Notice Number: NOT-AG-18-053 Key Dates Release Date: December 17, 2018 Related Announcements PAR-19-070 PAR-19-071 Issued National Institute Aging NIA) Purpose Notice Information specifies high-priority topic interest PAR-19-070 Research Current Topics Alzheimer's Disease Its Related Dementias R01 Clinical Trial Optional)" PAR-19-071 ldquo;Research Current Topics Alzheimer's Disease Its Related Dementias R21 Clinical Trial Allowed)”. Note applications proposing exploratory developmental projects which are insufficient preliminary data well certain focused secondary analysis projects should consider using R21 FOA, whereas projects already sufficient preliminary data a very strong well-developed scientific premise should the R01 FOA. Major Opportunities Research Epidemiology Alzheimer's Disease Related Dementias Cognitive Resilience Background etiology Alzheimer’s disease related dementias AD/ADRD) proven be complex expected. Our existing cohort studies both AD/ADRD cognitive aging include social, behavioral, cognitive, neuroimaging, biomarker, genetic, epigenetic, other measures assessed longitudinally collected initially ever earlier the lifespan. Indeed, is becoming clear both risk protective factors include exposures experiences early mid-life, long before appearance any neuropathology notable cognitive decline. Continued progress the epidemiology both AD/ADRD cognitive resilience therefore likely require cohorts, diverse cohorts, participants, variables, more occasions measurement. Additionally, greater collaboration among diverse scientific disciplines be needed. Research Objectives high-priority topic encourages investigator-initiated research all aspects cognitive epidemiology relevant AD/ADRD cognitive resilience identifies specific areas build current efforts supported NIA new recommendations the 2018 Alzheimer’s Disease Research Summit see: https://www.nia.nih.gov/research/administration/recommendations-nih-ad-r... for information). following areas of particular interest the NIA. Augmenting existing longitudinal cohort studies National Institutes Health NIH) supports broad range population studies address questions related the trajectory Alzheimer’s disease other aging phenotypes. collection analysis new phenotypic information, including not limited new biomarkers, neuroimaging, non-traditional data modalities such that wearable sensors, broaden impact existing studies. addition genetic data existing newly collected cohorts the light existing novel phenotypes allow analyses how specific genetic variants polygenic risk scores contribute the risk or protection against AD/ADRD the trajectory cognitive performance. emerging opportunities stem the wider availability electronic health records administrative data e.g., CMS Medicare claims) the ability collect phenotypic data online lower cost. Enabling precision medicine AD/ADRD through deep molecular phenotyping precision-medicine approach see: http://www.nih.gov/precisionmedicine/) presents new opportunities understanding molecular determinants AD/ADRD risk cognitive resilience diverse populations at level the individual. Notice invites applications will enhance potential community-based cohort studies enable precision medicine AD/ADRD by, example: expanding types cross-sectional longitudinal ante- post-mortem-biospecimen data-collection needed generate multiple layers ldquo;omics” data; incorporating dense molecular endophenotyping e.g., genomic, epigenomic, proteomic, metabolomic, microbiomic); collecting nontraditional data modalities using wearable sensors mobile-health technologies; embedding biomarkers environmental exposure geocodes. large-scale multidimensional data generated the above approaches serve the basis future systems biology gene-environment studies the development a new taxonomy AD/ADRD prevention. Enhancing power multiethnic cohort studies. multi-factorial etiology heterogeneity AD/ADRD reveal itself racial ethnic differences overall AD/ADRD risk in putative risk protective factors in progression neuropathology. Although multi-ethnic cohorts be very informative, well-powered cohort studies needed identify specific risk protective factors vary between sub)populations. cohorts also benefit the addition measures may better help us identify determinants both disease risk cognitive resilience. 2015 Alzheimer’s Disease Research Summit includes recommendation establish new cohorts intense endophenotyping are sufficiently powered analyze effects gender diverse populations. Exploring trends the risk AD/ADRD their explanation via putative risk protective factors. Recent research well-characterized cohorts suggests age-specific risk AD/ADRD be declining some populations increasing others. answer the trend question clear implications public health policy. Trend data also provide potentially powerful to test whether putative risk protective factors truly causal. example, educational attainment appears be protective against AD/ADRD whereas both cardiovascular disease CVD) female sex confer additional risk. the reasons these observed patterns not yet clear. risk posed female sex status, example, reflect sex differences affecting disease process, may include differences the trajectory hormonal changes age in sex chromosome, gender differences educational attainment all these. Comparisons between cohorts differing these factors over time be informative may require sophisticated analyses meta-analyses replication plans. Collecting sequencing DNA samples well-characterized cases controls. Research conducted investigators the Alzheimer’s Disease Sequencing Project ADSP; see: https://www.niagads.org/adsp/content/home) others demonstrated value whole-genome whole-exome sequencing the detection genetic variants may modify AD risk protection. sequencing more genomes well-characterized cases controls family based cohorts large multiply-affected families accelerate gene discovery target identification efforts to accelerate progress the drug development pipeline. Well-characterized subjects diversity sample sets especially needed augment statistical power. Applicants interested this line research should aware current emerging NIH guidance respect sharing genomic data see: http://gds.nih.gov/) are expected facilitate rapid data-sharing according existing ADSP NIA policies, include providing types data the ADSP NIAGADS/dbGaP database https://www.niagads.org/adsp/). Electronic archiving cohort studies Although NIH encourages broad inclusive data-sharing large studies, electronic archiving data many longitudinal cohorts either incomplete relies data infrastructure is vulnerable research-funding lapses. current NIH Strategic Plan Data Science see: https://datascience.nih.gov/strategicplan for additional information) focuses enhancing discoverability usability data sets developing appropriate analysis tools, providing special opportunities collaboration between epidemiologists survey scientists the hand computer data scientists the other. addition a wealth information relevant cognitive epidemiology is trapped non-digitized obsolete formats, are highly relevant data sets biospecimen collections have never publicly shared well surveys where greater availability paradata metadata benefit researchers. welcome applications will more data available use the research community expeditiously possible, likewise encourage dissemination efforts enhance discoverability these data. Harmonizing complex data sets relevant AD/ADRD Although have substantial efforts NIH develop brief, reliable measures e.g., PROMIS® the NIH Toolbox®; see: https://www.nihpromis.org for information) well recommendations the of off-the-shelf phenotypic measures e.g., PhenX) large epidemiological studies, has less work creating crosswalks between measures those have historically used cohort studies. need harmonization across platforms particularly acute studies include longitudinal clinical, neuroimaging, genetic genomic, biomarker data are costly obtain. Coordination harmonization data existing cohort studies the Alzheimer’s Disease Neuroimaging Initiative ADNI; see: http://www.adni-info.org/ more), Accelerating Medicines Partnership AMP) effort AD/ADRD see: http://www.nih.gov/science/amp/alzheimers.htm), the ADSP see: https://www.niagads.org/adsp/content/home) also welcome. Harmonizing dementia assessment enhance cross-national comparisons. important harmonization to study dementia trends the risk protective factors against dementia) differ between cohorts, work needed the harmonization dementia-assessment methods could inform cross-national comparisons. requires than simple translation instruments, since even best ones not operate equivalently developing countries where literacy rates levels educational attainment much lower. recent examples where work being done the 10/66 Dementia Research Group see: https://www.alz.co.uk/1066/default.php) lower income countries more recent work done within US-based Health Retirement Study HRS; see: http://hrsonline.isr.umich.edu/). Both examples a harmonized cognitive assessment protocol HCAP) can used compare dementia prevalence higher- lower-income countries. Applications use extend approaches develop new approaches harmonize dementia assessment suitable cross-national comparisons feasible both clinical field settings encouraged. Inquiries Please direct inquiries to: Dallas W. Anderson, Ph.D. Division Neuroscience  National Institute Aging NIA) Telephone: 301-496-1494  Email: dallas.anderson@nih.gov Jonathan W. King, Ph.D. Division Behavioral Social Research  National Institute Aging NIA)  Telephone: 301-402-4156  Email: kingjo@nia.nih.gov

data science
Notice of Updates to the IMAG Multiscale Modeling Initiative (PAR-15-085)

NOT-EB-16-011

NIBIB

Dec 22 2016

N/A

Notice Updates the IMAG Multiscale Modeling Initiative PAR-15-085) Notice Number: NOT-EB-16-011 Key Dates Release Date: December 22, 2016   Related Announcements PAR-15-085 Issued National Institute Biomedical Imaging Bioengineering NIBIB) National Cancer Institute NCI) National Heart, Lung, Blood Institute NHLBI) National Human Genome Research Institute NHGRI) National Institute Aging NIA) National Institute Alcohol Abuse Alcoholism NIAAA) National Institute Arthritis Musculoskeletal Skin Diseases NIAMS) Eunice Kennedy Shriver National Institute Child Health Human Development NICHD) National Institute Drug Abuse NIDA) National Center Complementary Integrative Health NCCIH) National Institute Environmental Health Sciences NIEHS) Office Behavioral Social Sciences Research OBSSR) U.S. Army Research Office ARO) - Biomathematics Department Energy DOE) - Office Science, Biological Environmental Research Program (BER) U.S. Food Drug Administration (FDA) – Office In-Vitro Diagnostics Radiological Health OIR), CDRH U.S. Food Drug Administration FDA) – Office Device Evaluation ODE), CDRH U.S. Food Drug Administration FDA) – Office Science Engineering Laboratories OSEL), nbsp;CDRH National Science Foundation NSF) - Directorate Computer amp; Information Science amp; Engineering CISE) National Science Foundation NSF) - Directorate Engineering ENG) National Science Foundation NSF) - Directorate Mathematical Physical Sciences MPS) National Aeronautics Space Administration NASA) - Human Research Program HRP) Office Naval Research ONR) - Division 311 nbsp; Purpose purpose this Notice to clarify programmatic goals specific interests the interagency funding opportunity announcement FOA) PAR-15-085, Predictive Multiscale Models Biomedical, Biological, Behavioral, Environmental Clinical Research U01).  application submission process remain same.  Notice providing additional information to: 1) express particular interest applications proposing development non-standard mathematical, statistical computational modeling methods address multiscale modeling research challenges would benefit joint interagency funding.  2) update Specific Interests the 22 participating funding components the associated Scientific/Research contacts.  1) funding components the seven funding agencies very interested jointly funding integrated research efforts incorporating research non-standard multiscale modeling methods within single project.  Applicants strongly encouraged submit applications develop multiscale models are high risk, push boundaries novel multiscale modeling methodologies. Applications should emphasize addressing multiscale modeling methodological challenges, while using domain applications testbeds addressing challenges. 2) Specific Interests section below lists updated interest statements all 22 funding components.  Below, excerpted statements the six non-NIH funding components, describing examples non-standard multiscale modeling methods: ARO:  innovative modeling methods, especially traditionally quot;pure" areas mathematics such topology, differential geometry, algebra DOE:  new methods characterizing imaging molecular systems, to synthesize redesign biology processes FDA:  models predict whether proposed medical product design function properly safely NASA:  overall conceptual framework organizing principle which might better understand the organism a whole responds space flight NSF:  Advances methods tools predictive modeling, simulation, analysis emergent behavior complex multiscale systems of interest, including issues verification, validation, uncertainty quantification across scales. ONR:  Basic research modeling dynamical properties networks determining causal effects influences needed networks interconnected nodes such social biological/neural networks would helpful the applicants identify agencies may interest specific research efforts within potential research proposal. Applicants strongly encouraged consult the Scientific/Research contacts based the Specific Interests the participating funding components. of 22 funding components participating this FOA involved contributing the review funding process; reserves right fund not fund those efforts regardless decisions other agencies. nbsp;For those applications are selected potential joint funding non-NIH funding components, PD/PI be requested submit same application directly interested funding agencies after review completed.  Specific Interests: following section describes updated specific interests two the 22 participating funding components this FOA. interests examples are limited these cases. Applicants strongly encouraged see full listing Specific Interests the guidelines Section I) contact funding components. U.S. Army Research Office ARO), Biomathematics Program interested basic, high-risk, high-reward research uses, develops, analyzes mechanistic multiscale mathematical models uncover fundamental relationships a wide variety biological systems. models use mathematical techniques fields traditionally used modeling, such probability, dynamical systems, partial differential equations, innovative modeling methods especially traditionally quot;pure" areas mathematics such topology, differential geometry, algebra. particular interest currently projects use mathematical modeling find commonalities mechanism between different biological systems that express underlying principles mathematical terms, well research taking advantage recent advances neuroscience newly-available experimental data gain fundamental understanding brain physiology, cognition, neurological disease through multiscale modeling. Office Naval Research ONR) Mathematical Data Science MDS) Program concerned basic research mathematics, probability statistics, signal processing, machine learning, data engineering, information theory.  program aims develop rigorous mathematical algorithmic answers questions are currently addressed using heuristics non-principled approaches. Recent advances technology led the era massive data sets are only larger, both terms sample size dimensionality the data, also complex. data be multi-modal, multi-relational gathered different sources. massive data sets (“Big Data”) introduce unique computational statistical challenges require development new theoretical principles can extend inference learning algorithms massive scales. outstanding question the MDS program addressing how balance tradeoff between computational accuracy computational resources analyzing large complex datasets.  of most challenging datasets include networks interconnected nodes such social biological/neural networks. Basic research modeling dynamical properties networks determining causal effects influences needed this area. In addition, program interested addressing challenges collaborative decision making developing crowdsourcing methods solving complex problems. application ONR should include full work the budget corresponding only tasks associated the interests the MDS program. Furthermore, is responsibility the applicants provide justification the interagency funding support. Specifically, applicant should explain why interagency support needed how the efforts are funded different agencies benefit effort is targeting MDS program. Proposers encouraged contact Program Officer discuss research interest prior the submission formal proposals. Prior Consultation Scientific/Research Staff Consultation relevant Scientific/Research staff strongly encouraged, later the Letter Intent due date. is the same the Letter Intent, should included a separate communication the Scientific/Research Contacts, Section VII.  requested the applicants, staff advise whether proposed project meets goals this FOA.  Staff not evaluate technical scientific merit the proposed project; technical scientific merit be determined during peer review using review criteria indicated this FOA. During consultation phase, the proposed project does meet programmatic needs this FOA, applicants be strongly encouraged consider Funding Opportunities.  Inquiries Please direct inquiries to: Grace Peng, Ph.D. National Institute Biomedical Imaging Bioengineering NIBIB) Telephone: 301-451-4778 Email: grace.peng@nih.gov Jennifer Couch, Ph.D. National Cancer Institute NCI) Telephone: 240-276-6210 Email: couchj@ctep.nci.nih.gov Wen Chen, Ph.D. National Center Complementary Integrative Health NCCIH) Telephone: 301-451-3989 Email: chenw@mail.nih.gov Pankaj Qasba, Ph.D. National Heart, Lung Blood Institute NHLBI) Telephone: 301-435-0050 Email: qasbap@nhlbi.nih.gov Michael J. Pazin, Ph.D. National Human Genome Research Institute NHGRI) Telephone: 301-496-7531 Email: pazinm@mail.nih.gov Coryse St. Hillaire-Clarke, Ph.D. National Institute Aging NIA) Telephone: 301-496-9350 Email: sthillaireclacn@mail.nih.gov Gregory Bloss, M.A., M.P.P. National Institute Alcohol Abuse Alcoholism NIAAA) Telephone: 301-443-3865 Email: Gregory.Bloss@nih.gov Gayle Lester, Ph.D. National Institute Arthritis Musculoskeletal Skin Diseases NIAMS) Division Musculoskeletal Diseases Telephone: 301-594-3511 Email: lester1@mail.nih.gov Hung Tseng, Ph.D. National Institute Arthritis Musculoskeletal Skin Diseases NIAMS) Division Skin Rheumatic Disease Telephone: 301-594-5032 Email: tsengh@mail.nih.gov Regina Bures, Ph.D. Eunice Kennedy Shriver National Institute Child Health Human Development NICHD) Email: buresrm@mail.nih.gov Susan Volman, Ph.D. National Institute Drug Abuse NIDA) Telephone: 301-435-1315 Email: svolman@nida.nih.gov David Balshaw, PhD National Institute Environmental Health Sciences NIEHS) Telephone: 919-541-2448 Email: balshaw@niehs.nih.gov Bill Riley, Ph.D. Office Behavioral Social Science Research OBSSR) Telephone: 301-402-1146 Email: william.riley@nih.gov Virginia B. Pasour, PhD U.S. Army Research Office ARO) Telephone: 919-549-4254 Email: virginia.b.pasour.civ@mail.mil Ramana Madupu, Ph.D. Department Energy DOE), Biological Environmental Research Telephone: 301-366-2916 Email: ramana.madupu@science.doe.gov Donna R. Lochner Food Drug Administration FDA) Telephone: 301-796-6309 Email: donna.lochner@fda.hhs.gov Mary Ann Horn, Ph.D. National Science Foundation, Directorate Mathematical Physical Sciences NSF-MPS) Telephone: 703-292-4879 Email: mhorn@nsf.gov Vipin Chaudhary, Ph.D. National Science Foundation, Directorate Computer amp; Information Science amp; Engineering NSF-CISE) Telephone: 703-292-2254 Email: vipchaud@nsf.gov Michele Grimm, Ph.D. National Science Foundation, Directorate Engineering NSF-ENG) Telephone: 703-292-4641 Email: mgrimm@nsf.gov Pedja Neskovic, Ph.D. Office Naval Research ONR) Telephone: 703-696-4304 Email: predrag.neskovic@navy.mil Jennifer Fogarty, Ph.D. National Aeronautics Space Administration NASA) Email: jennifer.fogarty-1@nasa.gov

data science, big data, computational, machine learning, neural networks
Notice of the Office of Strategic Coordination (Common Fund) Participation in RFA-ES-16-003 "BD2K Mentored Career Development Award in Biomedical

NOT-RM-16-024

Roadmap

May 17 2016

N/A

Notice the Office Strategic Coordination Common Fund) Participation RFA-ES-16-003 BD2K Mentored Career Development Award Biomedical Big Data Science Intramural Investigators K22)" Notice Number: NOT-RM-16-024 Key Dates Release Date: 17, 2016 Related Announcements RFA-ES-16-003   Issued Office Strategic Coordination Common Fund) Purpose purpose this Notice to inform potential applicants the Office Strategic Coordination Common Fund) participating, effective immediately, the following Funding Opportunity Announcement FOA): RFA-ES-16-003 quot;BD2K Mentored Career Development Award Biomedical Big Data Science Intramural Investigators K22)" RFA-ES-16-003 updated, accordingly, reflect Common Fund's participation this FOA. are changes the Funds Available Anticipated Number Awards due the funding structure this BD2K FOA. Part I. Overview Information Components Participating Organizations National Institute Environmental Health Sciences NIEHS) National Cancer Institute NCI) National Eye Institute NEI) National Human Genome Research Institute NHGRI) National Institute Aging NIA) National Institute Alcohol Abuse Alcoholism NIAAA) National Institute Allergy Infectious Diseases NIAID) National Institute Arthritis Musculoskeletal Skin Diseases NIAMS) Eunice Kennedy Shriver National Institute Child Health Human Development NICHD) National Institute Deafness Other Communication Disorders NIDCD) National Institute Dental Craniofacial Research NIDCR) National Institute Diabetes Digestive Kidney Diseases NIDDK) National Institute Drug Abuse NIDA) National Institute Mental Health NIMH) National Library Medicine NLM) National Center Complementary Integrative Health NCCIH) National Center Advancing Translational Sciences NCATS) Division Program Coordination, Planning Strategic Initiatives, Office Disease Prevention ODP) Division Program Coordination, Planning Strategic Initiatives, Office Research Infrastructure Programs ORIP) Office Behavioral Social Sciences Research OBSSR) Office Research Women’s Health ORWH) Office Strategic Coordination Common Fund) Catalog Federal Domestic Assistance CFDA) Number(s) 93.113; 93.398; 93.867; 93.172; 93.866; 93.273; 93.855; 93.856; 93.846; 93.865; 93.173; 93.121; 93.847; 93.279; 93.242; 93.879; 93.213; 93.350; 93.351; 93.313; 93.310 other sections this FOA remain same. Inquiries Please direct inquiries to: Leslie Derr, Ph.D. Office the Director OD) Telephone: 301 594-8174 Email: derrl@mail.nih.gov

data science, big data
Notice of the National Heart, Lung, and Blood Institute (NHLBI) Participation in RFA-MD-15-005 "NIH Big Data to Knowledge (BD2K) Enhancing Divers

NOT-HL-15-250

NHLBI

Jan 16 2015

N/A

Notice the National Heart, Lung, Blood Institute NHLBI) Participation RFA-MD-15-005 NIH Big Data Knowledge BD2K) Enhancing Diversity Biomedical Data Science R25)" Notice Number: NOT-HL-15-250 Key Dates Release Date: January 16, 2015 Related Announcements RFA-MD-15-005 Issued National Heart, Lung, Blood Institute NHLBI) Purpose purpose this Notice to inform potential applicants the National Heart, Lung, Blood Institute NHLBI) participating, effective immediately, RFA-MD-15-005, quot;NIH Big Data Knowledge BD2K) Enhancing Diversity Biomedical Data Science R25)". following sections RFA-MD-15-005 been updated reflect NHLBI's participation this funding opportunity announcement. Part 1.  Overview Information Components Participating Organizations National Institute Minority Health Health Disparities NIMHD) National Cancer Institute NCI) National Human Genome Research Institute NHGRI) National Institute Aging NIA) National Institute Alcohol Abuse Alcoholism NIAAA) National Institute Allergy Infectious Diseases NIAID) National Institute Arthritis Musculoskeletal Skin Diseases NIAMS) National Institute Biomedical Imaging Bioengineering NIBIB) Eunice Kennedy Shriver National Institute Child Health Human Development NICHD) National Institute Deafness Other Communication Disorders NIDCD) National Institute Dental Craniofacial Research NIDCR) National Institute Diabetes Digestive Kidney Diseases NIDDK) National Institute Drug Abuse NIDA) National Institute General Medical Sciences NIGMS) National Institute Mental Health NIMH) National Institute Neurological Disorders Stroke NINDS) National Institute Nursing Research NINR) National Library Medicine NLM) National Center Complementary Alternative Medicine NCCAM) National Center Advancing Translational Sciences NCATS) Division Program Coordination, Planning Strategic Initiatives Office Research Infrastructure Programs ORIP) Office Behavioral Social Sciences Research OBSSR) Office Strategic Coordination Common Fund) National Heart, Lung, Blood Institute NHLBI) Catalog Federal Domestic Assistance CFDA) Numbers 93.307; nbsp;93.350;  93.213; 93.398; 93.399; 93.172; 93.866; 93.273; 93.855; 93.856; 93.846; 93.286; 93.865; 93.279; 93.173; 93.121; 93.847; 93.859; 93.242; 93.853; 93.361; 93.879; 93.351; 93.310; 93.394; 93.395; 93.396; 93.397; 93.399; 93.837; 93.838; 93.839; 93.233 Inquiries Please direct inquiries to: Weiniu Gan, Ph.D. National Heart, Lung, Blood Institute NHLBI) Telephone: 301-435-0202 Email: ganw2@mail.nih.gov nbsp;

data science, big data
Notice of Special Interest (NOSI): Computational and Statistical Methods to Enhance Discovery from Health Data

NOT-LM-19-003

NLM

Mar 19 2019

N/A

Notice Special Interest NOSI): Computational Statistical Methods Enhance Discovery Health Data Notice Number: NOT-LM-19-003 Key Dates Release Date: March 19, 2019 Related Announcements PAR-18-896 Issued National Library Medicine NLM) Purpose National Library Medicine issuing Notice highlight interest receiving grant applications through NLM Research Grants Biomedical Informatics Data Science R01 Clinical Trial Optional) PAR 18-896), focused research reduce mitigate gaps errors health data sets. Background Recent successes the of data-centric artificial intelligence AI) methods such deep learning stimulating interest the promise harnessing large complex digital health data sets advance goals precision medicine. Applying AI methods large health data sets promises provide new powers discovery, diagnosis, prediction, decision support aimed improving health outcomes reducing healthcare costs. Numerous public datasets human non-human data available, a rich array specialized tools platforms be used studies applications. However, recent work identifying addressing systematic biases blind spots data, in AI systems derived that data, highlighted array potential problems fairness, accuracy, safety, reproducibility inferences conclusions. Work bias incompleteness health data sets includes studies find poor representation minority groups, seniors, women. See, example, https://www.eurekalert.org/pub_releases/2016-10/uoms-nsr100716.php, or https://datasociety.net/output/fairness-in-precision-medicine/?utm_sourc...). recent Wall Street Journal article https://www.wsj.com/articles/a-crucial-step-for-avoiding-ai-disasters-11...) noted computational tools developed a diverse team help avoid bias algorithms. Beyond problems biases other gaps data, research using health data humans requires special care protect sources the data see https://www.ncbi.nlm.nih.gov/pubmed?term=Barocas%2C%20Solon%5BAuthor%5D ). All Us Research Program https://allofus.nih.gov/) aims develop unbiased, representative health data resource, there many health data sets already use being constructed. Tools developed using biased incomplete data sets contribute erroneous analyses. Statistical fallacies representational errors unrelated the research question hand introduce systematic errors. core questions understanding mitigating and problems health data research are: can done, computationally and/or statistically, reduce mitigate gaps errors data sets used health research?" and, can improve tools used discovery, understanding, visualization health data sets their analyses?" Whether problem due incomplete health data inadequate tools, approaches needed strengthen reproducibility applicability data-centered research the etiology, epidemiology treatment health conditions. Research Objectives NLM invites research grant applications propose state the art methods approaches address problems large health data sets tools used analyze them, whether data drawn electronic health records public health data sets, biomedical imaging, omics repositories other biomedical social/behavioral data sets. Areas interest include are limited 1) developing testing computational statistical approaches applied large and/or merged health data sets holding human non-human data, a focus understanding characterizing gaps, errors, biases, other limitations the data inferences based the data; 2) exploring approaches correcting biases compensating missing data, including introduction debiasing techniques policies the of synthetic data; 3) testing new statistical algorithms other computational approaches strengthen research designs use specific types biomedical social/behavioral data; 4) generating metadata adequately characterizes data, including provenance, intended use, processes which was collected verified; 5) improving approaches integrating, mining, analyzing health data preserve confidentiality, accuracy, completeness overall security the data. Applicants should address ethical issues might arise their proposed approach. Application Submission Information Applications response this Notice must submitted through NLM’s funding opportunity announcement, PAR-18-896: NLM Research Grants Biomedical Informatics Data Science R01 Clinical Trial Optional). instructions PAR-18-896 must followed. Submissions should indicate they in response NOT-LM-19-003 Field 4.b the SF 424 R&R form. Program Directors/Principal Investigators PDs/PIs) planning submit applications this topic strongly encouraged contact scientific contact listed this Notice advice the appropriateness a potential application alignment NLM’s program priorities. Inquiries Please direct inquiries to: Alan Vanbiervliet, PhDNational Library Medicine/Extramural ProgramsTelephone: 301-594-4882Email: alan.vanbiervliet@nih.gov

data science, computational, informatics, artificial intelligence, deep learning
Notice of Participation of the Office of Research Infrastructure Programs in PA-14-157 Early Stage Development of Technologies in Biomedical Computing

NOT-OD-15-157

ORIP

Sep 23 2015

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Notice Participation the Office Research Infrastructure Programs PA-14-157 Early Stage Development Technologies Biomedical Computing, Informatics, Big Data Science R41/R42)" Notice Number: NOT-OD-15-157 Key Dates Release Date: September 23, 2015 Related Announcements PA-14-157     Issued Division Program Coordination, Planning Strategic Initiatives, Office Research Infrastructure Programs ORIP) Purpose purpose this Notice to inform potential applicants the Office Research Infrastructure Programs ORIP) participating, effective immediately, PA-14-157 quot;Early Stage Development Technologies Biomedical Computing, Informatics, Big Data Science R41/R42)". following sections PA-14-157 been updated reflect ORIP participation this Funding Opportunity Announcement FOA.) Part 1.  Overview Information  Components Participating Organizations National Institute General Medical Sciences NIGMS) National Human Genome Research Institute NHGRI) National Institute Alcohol Abuse Alcoholism NIAAA) National Institute Allergy Infectious Diseases NIAID) National Institute Arthritis Musculoskeletal Skin Diseases NIAMS) National Institute Biomedical Imaging Bioengineering NIBIB) Eunice Kennedy Shriver National Institute Child Health Human Development NICHD) National Institute Drug Abuse NIDA) National Institute Environmental Health Sciences NIEHS) National Institute Mental Health NIMH) National Institute Neurological Disorders Stroke NINDS) National Institute Nursing Research NINR) National Library Medicine NLM) National Cancer Institute NCI) Division Program Coordination, Planning Strategic Initiatives, Office Research Infrastructure Programs ORIP) Catalog Federal Domestic Assistance CFDA) Number(s) 93.859; 93.273; 93.361; 97.853; 93.286; 93.865; 93.846; 93.172; 93.113; 93.242; 93.879; 93.855; 93.856; 93.279; 93.393; 93.394; 93.395; 93.396; 93.399; 93.351 Part 2. Full Text Announcement Section VII. Agency Contacts Scientific/Research Contact(s) Miguel Contreras, Ph.D. Office Research Infrastructure Programs ORIP) Telephone: 301-594-9410 Email: contre1@mail.nih.gov Financial/Grants Management Contact(s) Artisha Y. Eatmon   National Center Advancing Translational Sciences NCATS) Office Research Infrastructure Programs ORIP) Telephone: 301-435-0845 Email: artisha.eatmon@nih.gov other changes made this FOA. Inquiries Please direct inquiries to: Miguel Contreras, Ph.D. Office Research Infrastructure Programs ORIP) Telephone: 301-594-9410 Email: contre1@mail.nih.gov

data science, big data, informatics
Notice of Participation of the Office of Research Infrastructure Programs in PA-14-154 "Early Stage Development of Technologies in Biomedical Com

NOT-OD-15-161

ORIP

Sep 24 2015

N/A

Notice Participation the Office Research Infrastructure Programs PA-14-154 Early Stage Development Technologies Biomedical Computing, Informatics, Big Data Science R43/R44)" Notice Number: NOT-OD-15-161 Key Dates Release Date:   September 24, 2015 Related Announcements PA-14-154 Issued Division Program Coordination, Planning Strategic Initiatives, Office Research Infrastructure Programs ORIP) Purpose purpose this Notice to inform potential applicants the Office Research Infrastructure Programs ORIP) participating, effective immediately, PA-14-154 quot;Early Stage Development Technologies Biomedical Computing, Informatics, Big Data Science R43/R44)". following sections PA-14-154 been updated reflect ORIP participation this FOA. Part 1.  Overview Information Components Participating Organizations National Institute General Medical Sciences NIGMS) National Human Genome Research Institute NHGRI) National Institute Alcohol Abuse Alcoholism NIAAA) National Institute Allergy Infectious Diseases NIAID) National Institute Arthritis Musculoskeletal Skin Diseases NIAMS) National Institute Biomedical Imaging Bioengineering NIBIB) Eunice Kennedy Shriver National Institute Child Health Human Development NICHD) National Institute Dental Craniofacial Research NIDCR) National Institute Drug Abuse NIDA) National Institute Environmental Health Sciences NIEHS) National Institute Mental Health NIMH) National Institute Neurological Disorders Stroke NINDS) National Institute Nursing Research NINR) National Library Medicine NLM) National Cancer Institute NCI) Division Program Coordination, Planning Strategic Initiatives, Office Research Infrastructure Programs ORIP) Catalog Federal Domestic Assistance CFDA) Number(s) 93.859; 93.273; 93.361; 97.853; 93.286; 93.865; 93.846; 93.172; 93.113; 93.242; 93.879; 93.855; 93.856; 93.279; 93.393; 93.394; 93.395; 93.396; 93.399; 93.351 Part 2. Full Text Announcement Section VII. Agency Contacts Scientific/Research Contact(s) Miguel Contreras, Ph.D. Office Research Infrastructure Programs ORIP) Telephone: 301-594-9410 Email: contre1@mail.nih.gov Financial/Grants Management Contact(s) Artisha Y. Eatmon   National Center Advancing Translational Sciences NCATS) Office Research Infrastructure Programs ORIP) Telephone: 301-435-0845 Email: artisha.eatmon@nih.gov other aspects this FOA remain same. Inquiries Please direct inquiries to: Miguel Contreras, Ph.D. Office Research Infrastructure Programs ORIP) Telephone: 301-594-9410 Email: contre1@mail.nih.gov

data science, big data, informatics

Pages

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