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
The KUH Predoctoral to Postdoctoral Fellow Transition Award (F99/K00 Clinical Trial Not Allowed)

RFA-DK-18-024

NIDDK

Jan 28 2019

Nov 21 2019

The purpose of the KUH/NIDDK Predoctoral to Postdoctoral Fellow Transition Award (F99/K00) is to recruit exceptional graduate students who are recognized by their institutions for their high potential and to incentivize them to pursue a Kidney, Urologic or Hematologic (K, U, or H) postdoctoral position that ultimately positions them to become independent K, U, or H researchers. This two-phase award will facilitate completion of the doctoral dissertation and stablize the transition of highly talented Ph.D candidates from a variety of fields, including, but not limited to, engineering, statistics, data science, imaging, biochemistry and genetics into strong postdoctoral appointments that are focused on K, U or H research. It is anticipated that successful completion of this phased award will make the individual highly competitive for a subsequent NIDDK award (e.g., K99/R00, R01). Opportunities for career development activities relevant to their long-term career goals of becoming independent researchers will be provided. Graduate students who are already involved in K, U, or H research are encouraged to apply for the NIDDK F31 (PA-18-671).
This Funding Opportunity Announcement (FOA) does not allow applicants to propose to lead an independent clinical trial, but does allow applicants to propose research experience in a clinical trial led by a sponsor or co-sponsor

data science
The Application of Big Data Analytics to Drug Abuse Research (R01 Clinical Trial Optional)

PA-18-057

NIDA

Nov 01 2017

May 08 2019

The purpose of this FOA is to encourage the application of Big Data analytics to reveal deeper or novel insights into the biological and behavioral processes associated with substance abuse and addiction.NIDA recognizes that to accelerate progress toward understanding how the human brain and behavior is altered by chronic drug use and addiction, it is vital to develop more powerful analytical methods and visualization tools that can help capture the richness of data being generated from genetic, epigenetic, molecular, proteomic, metabolomic, brain-imaging, micro-electrode, behavioral, clinical, social, services, environmental studies as well as data generated from electronic health records.Applications for this FOA should develop and/or utilize computational approaches for analyzing large, complex datasets acquired from drug addiction research.The rapid increase of technologies to acquire unprecedented amounts of neurobiological and behavioral data, and an expanding capacity to store those data, results in great opportunity to bring to bear the power of the computational methods of Big Data analytics on drug abuse and addiction.

data science, big data, computational, bioinformatics, machine learning
T32 Training Program for Institutions That Promote Diversity (T32 Clinical Trial Not Allowed)

RFA-HL-19-023

NHLBI

Apr 27 2018

May 07 2021

The purpose of this funding opportunity announcement (FOA) is to enhance the participation of individuals from diverse backgrounds underrepresented in cardiovascular, pulmonary, hematologic and sleep disorders research across the career development continuum. The NHLBIs T32 Training Program for Institutions That Promote Diversity is a Ruth L. Kirschstein National Research Service Award Program intended to support training of predoctoral and health professional students and individuals in postdoctoral training institutions with an institutional mission focused on serving health disparity populations not well represented in scientific research, or institutions that have been identified by federal legislation as having an institutional mission focused on these populations, with the potential to develop meritorious training programs in cardiovascular, pulmonary, and hematologic diseases, and sleep disorders. The NHLBIs T32 Training Program for Institutions That Promote Diversity is designed to expand the capability for biomedical research by providing grant support to institutions that have developed successful programs that promote diversity, serve health disparity populations, and that offer doctoral degrees in the health professions or in health-related sciences. These institutions are uniquely positioned to engage minority and other health disparity populations in research, translation, and implementation of research advances that impact health outcomes, as well as provide health care for these populations. This Funding Opportunity Announcement (FOA) does not allow appointed Trainees to lead an independent clinical trial, but does allow them to obtain research experience in a clinical trial led by a mentor or co-mentor.

data science, big data, quantitative science, bioinformatics
Stimulating Access to Research in Residency (StARR) (R38)

RFA-HL-18-023

NHLBI

Aug 23 2017

May 13 2020

The purpose of this program is to recruit and retain outstanding, postdoctoral-level health professionals who have demonstrated potential and interest in pursuing careers as clinician-investigators. To address the growing need for this critical component of the research workforce, this funding opportunity seeks applications from institutional programs that can provide outstanding mentored research opportunities for Resident-Investigators and foster their ability to transition to individual career development research awards. The program will support institutions to provide support for up to 2 years of research conducted by Resident-Investigators in structured programs for clinician-investigators with defined program milestones.

data science, bioinformatics
Single Cell Opioid Responses in the Context of HIV (SCORCH) Program: Data Coordination, Analysis, and Scientific Outreach (UM1 Clinical Trial Not All

RFA-DA-19-038

NIDA

Apr 01 2019

May 09 2019

Along with RFA-DA-19-037, which will support the generation of single cell datasets for one or more brain regions relevant to opioid use disorder and persistent HIV infection, a data coordination/analysis/outreach center (RFA-DA-19-038) will be established to make NIDA-funded single cell data and other molecular HIV/SUD data FAIR (Findable, Accessible, Interoperable, and Reusable). Harmonized single cell HIV/SUD data sets will enable immediate data mining by the scientific community for HIV and/or SUD biomarkers and potential pathways for therapeutic intervention. It will also enable future mining of these data sets as new and improved data science and information technology approaches are developed, maximizing NIDAs original investment in the data generating activities.

data science, data integration, common data, artificial intelligence, machine learning
Short-Term Research Education Program to Increase Diversity in Health-Related Research (R25 Clinical Trial Not Allowed)

RFA-HL-19-024

NHLBI

May 01 2018

May 07 2021

The NIH Research Education Program (R25) supports research education activities in the mission areas of the NIH. The over-arching goal of this NHLBI R25 program is to support educational activities that enhance the diversity of the biomedical, behavioral and clinical research workforce in the mission areas of importance to NHLBI.
To accomplish the stated over-arching goal, this FOA will support creative educational activities with a primary focus on Research Experiences

data science, big data, bioinformatics
RESCINDED - Notice of Intent to Publish a Funding Opportunity Announcement for Rare Disease Cohorts in Heart, Lung, Blood and Sleep Disorders (UG3/UH3

NOT-HL-18-620

NHLBI

Apr 13 2018

N/A

Notice Intent Publish Funding Opportunity Announcement Rare Disease Cohorts Heart, Lung, Blood Sleep Disorders UG3/UH3) Notice Number: NOT-HL-18-620 Key Dates Release Date: April 13, 2018 RESCINDED) Estimated Publication Date Funding Opportunity Announcement: 12/01/2018 First Estimated Application Due Date:02/01/2019 Earliest Estimated Award Date:10/31/2019 Earliest Estimated Start Date:12/31/2019 Related Announcements None Issued National Heart, Lung, Blood Institute NHLBI) Purpose National Heart, Lung Blood Institute intends promote new initiative establish cohorts rare heart, lung, blood, and/or sleep HLBS) diseases enables multidisciplinary teams conduct natural history mechanistic studies provide evidence base future clinical trials improved diagnostics.  studies help advance fundamental insights key molecular, genomic, clinical, environmental behavioral determinants rare HLBS diseases their outcomes leading diagnostic therapeutic strategies.   NHLBI interested applications will address questions relevant the NHLBI mission, address gaps the NHLBI?s portfolio rare disease cohorts that align the Institute ' s Strategic Vision https://www.nhlbi.nih.gov/about/documents/strategic-vision). NHLBI intends to utilize UG3/UH3 activity code, bi-phasic, milestone-driven cooperative agreement. Details the planned FOA provided below. Notice being provided allow potential applicants sufficient time develop responsive proposals.  FOA expected be published October 2018 anticipated application receipt dates February 2019 February 2020. Research Initiative Details planned initiative provide opportunities efficiently advance rare disease research using genetics deep phenotyping characterize disease to identify disease sub-types; use data science methods integrate clinical patient-reported outcomes PROs) laboratory, imaging omics data understand natural history disease;  generate data differentiate patients the same morphological phenotype different genetic mutations  severity outcomes; elucidate genotype-phenotype interactions multisystem phenotyping develop reliable valid predictive tools determine will respond which treatments when intervene; to encourage innovative methods such telemedicine reach subjects rare diseases located remote locations without access a major academic medical center. goal this initiative to encourage creative innovative research; such, applications should propose studies investigating hypotheses research questions currently addressed cohorts funding the NHLBI. RFA invite applications propose cohorts are created de novo or re-establish study populations enrolling patients previously-funded cohorts, clinical trials registries. Funding Information Estimated Total Funding 1,625,000 Total Costs) Expected Number Awards 4 Estimated Award Ceiling 500,000 Direct Costs) Primary CFDA Numbers 93.837, 93.838, 93.839, 93.840, 93.233 Anticipated Eligible Organizations Public/State Controlled Institution Higher Education Private Institution Higher Education Nonprofit 501(c)(3) IRS Status than Institution Higher Education) Nonprofit without 501(c)(3) IRS Status than Institution Higher Education) Small Business For-Profit Organization than Small Business) State Government Indian/Native American Tribal Government Federally Recognized) City township governments Indian/Native American Tribally Designated Organization Native American tribal organizations than Federally recognized tribal governments) Indian/Native American Tribal Government than Federally Recognized) Regional Organization  Applications not being solicited this time.   Inquiries Please direct inquiries to: Ellen M. Werner, PhD, MA  National Heart, Lung, Blood Institute  301-435-0065  wernere@nhlbi.nih.gov 

data science
REQUEST FOR PROPOSAL (RFP): BIOINFORMATICS RESOURCE CENTERS FOR INFECTIOUS DISEASES, RFP-NIAID-DMID-NIHAI201800005

NOT-AI-19-009

NIAID

Oct 15 2018

N/A

REQUEST PROPOSAL RFP): BIOINFORMATICS RESOURCE CENTERS INFECTIOUS DISEASES, RFP-NIAID-DMID-NIHAI201800005 Notice Number: NOT-AI-19-009 Key Dates Release Date:October 15, 2018 Related Announcements None Issued National Institute Allergy Infectious Diseases NIAID) Purpose National Institute Allergy Infectious Diseases NIAID), National Institutes Health NIH), the Department Health Human Services DHHS) supports research related the basic understanding microbiology immunology leading the development vaccines, therapeutics, medical diagnostics the prevention, treatment, diagnosis infectious immune-mediated diseases.   NIAID, Division Microbiology Infectious Diseases DMID) a requirement maintain Bioinformatics Resource Centers BRCs), have become critical resource data tools generated NIAID supported programs other publicly accessible data the infectious disease research community.   NIAID made significant investment funding basic clinical research projects are generating large, diverse complex data sets including genomics/omics data, clinical data, immune phenotyping assay data, imaging other data sets. infectious diseases immune mediated diseases communities become data-intense enterprise a priority NIAID to transform data knowledge understand pathogenesis, transmission, evolution the pathogen, pathogen-host interactions the host response infectious diseases inform development new improved diagnostics, therapeutics, vaccines. NIAID invested bioinformatics data science data generated NIAID intramural extramural communities has expanded activities data management systems, bioinformatics resource centers data repositories/knowledgebases have provided broad scientific community user friendly access open data analytical tools.   Since inception 2004, NIAID’s BRCs focused supporting providing genome sequence databases annotation microbial organisms. BRCs provided infectious disease research community publicly accessible systems store, update, integrate display genome sequence data its annotation, functional genomics other ldquo;omics” data, other associated data information a large variety human pathogens vectors human pathogens related microbial species strains. BRC systems allow users query analyze data. a result, BRCs become public repository primary resource data tools generated NIAID supported programs other publicly accessible data the infectious disease research community.   objective this solicitation to continue support the BRCs provide data-driven, production-level sustainable computational platform(s) enable sharing access usable re-usable data, portable computational tools standards support interoperability the infectious diseases research community. Through effort NIAID continue provide bioinformatics services training support large-scale, system level diverse data integration modeling, enable predictive biology pathogens host-pathogen interactions will accelerate discovery research, clinical investigation, therapeutic development infectious diseases. addition, platform infrastructure expected serve a model future NIAID systems. change the previous competition should noted: to 2) BRCs be awarded one 1) contract awarded bacterial species viral families one 1) contract awarded protozoan species, fungi invertebrate vectors human pathogens. Offerors propose one both data resources the group organisms. Funding under prior solicitation NOT required submission this solicitation.   is anticipated two 2) cost-reimbursement plus fixed-fee, level-of-effort, type contracts be awarded a one-year base period performance beginning or around September 1, 2019. Awards expected include four 4) one-year option periods. total period performance, including options, five 5) years. Government’s base level-of-effort requirement estimated 43,680 direct labor hours each contract period, equating 21 Full Time Equivalents FTEs) an FTE being defined 2,080 direct labor hours. addition the base level-of-effort, contract period shall contain option quantity up nine 9) additional FTEs.   NIAID recognizes a single organization institution not the full spectrum expertise facilities required perform activities set forth the Statement Work. Contractors need be supported a certain extent the expertise resources other organizations persons through consortia agreements, partnerships, subcontracts, and/or consultants. However, contractors shall responsible ALL work performed shall responsible project planning, initiation, implementation, management communication; evaluation, selection, management subcontractors; for deliverables specified this contract.   Any responsible Offeror submit proposal will considered the Agency. Request Proposal RFP) available electronically may accessed through FedBizOpps https://www.fbo.gov.  notice does commit Government award contract. collect calls be accepted. facsimile transmissions be accepted   this solicitation, NIAID requires proposals be submitted via 2) methods: 1) Disc CD DVD) 2) Online via NIAID electronic Contract Proposal Submission eCPS) website. content the disc online proposals must identical. Submission proposals facsimile e-mail not acceptable.   directions using eCPS, to website https://ecps.nih.gov and click ldquo;How Submit.” Inquiries Please direct inquiries to: Primary Contact: Brian Madgey National Institute Allergy Infectious Diseases NIAID) Telephone: 240-627-3712 Email: madgeyba@mail.nih.gov   Secondary Contact: Stanley Knight National Institute Allergy Infectious Diseases NIAID) Telephone: 240-669-5181 Email: knights@niaid.nih.gov

data science, computational, bioinformatics, data integration
Request for Information (RFI): Strengthening the Early Stages of the NIDA Training Pipeline through Massively Open Online Courses on the Biomedical In

NOT-DA-16-027

NIDA

Apr 12 2016

N/A

Request Information RFI): Strengthening Early Stages the NIDA Training Pipeline through Massively Open Online Courses the Biomedical Informatics Addiction Research Notice Number: NOT-DA-16-027 Key Dates Release Date:    April 12, 2016 Response Date: July 3, 2016 Related Announcements None     Issued National Institute Drug Abuse NIDA) Purpose Training next generation addiction researchers a critical priority the National Institute Drug Abuse NIDA).  need expertise biomedical informatics, statistics Big Data science increasing across of biomedical research, including addiction.  NIDA seeks create massive open online course MOOC) providing teaching materials begin training the next generation quantitative addiction researchers.  purpose this Request Information RFI) to seek broad public input the design the course, the best methods implementation. Background mission NIDA to lead nation bringing power science bear drug abuse addiction. Part fulfilling mission includes creating pipeline training opportunities ensure research workforce adequately skilled. need increased education statistics, informatics data science grown the development new technologies neuroscience biomedical research. MOOCs able reach audiences the thousands. are available online websites such Coursera EDx, offering huge advantage over local courses requiring travel.  are already MOOCs available focusing informatics neuroscience data analysis. However, are MOOCs biomedical informatics directly related addiction research.  specifically, NIDA interested strengthening training pipeline produce influx researchers trained these techniques providing MOOC-distributed training materials students and/or teachers. Information Requested RFI intended gather broad public input the biomedical informatics, statistics Big Data lecture topics deemed valuable training next generation addiction researchers the most appropriate methods distribute those topics.  Advice sought includes is limited the following items ranked priority NIDA, please provide feedback as as possible: Ideas the target audience:  NIDA considered advanced high school students have sophistication integrate materials related addiction research biomedical informatics.  example, includes ideas constraining audience those students considering experiences a research lab ideas the value broadly targeting students hopes exciting those considering experience a research lab. Ideas whether is appropriate constrain topic domain addiction, whether is valuable students early their training arc obtain broader biomedical informatics training spans disease areas. Ideas whether placing statistics biomedical informatics the context addiction research provides greater intuition. Ideas how MOOC materials fit existing curriculum:  example, a high school audience targeted, should MOOC integrated existing curriculum, used class a supplement such curriculum serve an outside activity such an after-school club. Ideas whether such course serve a virtual lab” students do have opportunity view analyze research data, are interested research related majors. Ideas whether such course serve a strength the resume students applying work labs the undergraduate level beyond, including community college/associate level. Ideas whether teachers should serve the primary viewers these online courses going through materials using to create customized curriculum their students. Ideas topic areas within biomedical informatics should included the MOOC. Ideas whether regression z-scores be suitable degree challenge high school students sought. Ideas whether multi-dimensional analysis machine learning suitable challenges pre-associates pre-baccalaureate levels targeted.  Ideas how lectures should MOOC comprised of, how long should lecture be: response or not provided consideration the above bullet lecture topics. Ideas whether funded research investigators are experts these areas should the presenters the MOOC lectures:  a high school audience sought, comment funded research investigators working high school teachers if the best to foster such collaborations. Ideas what media e.g. websites, technologies) should used disseminate materials. Insights format materials each individual lecture e.g. 1 video directed teachers, 1 video use students, data, handouts homework assignments). Insights the formatting the entire compiled course. NIDA collected following listing topics relevance advance biomedical informatics within addiction research.  Please comment these potential MOOC lecture topics what level education/aptitude should targeted towards.  Please also provide additional topics would prepare students early the training pipeline experiences the lab: Analysis voltammetry signaling; Longitudinal analysis calcium imaging microelectrode data over temporal course self-administration Analysis temporal geospatial data mHealth studies Construction correlation matrices during resting state fMRI tasks Epidemiological analysis national local drug Construction Manhattan plots genetics analysis Dimensionality reduction allowing visualization high-dimensional data; Single trial analyses other high-resolution investigations research data; Investigating individual variability self-administration behavioral data explore resilience vulnerability factors; Automated analysis machine learning classification big behavioral data," such multiple camera long-term video monitoring naturalistic behaviors e.g. the home cage setting), recording ultrasonic vocalizations other behavioral measures; Analysis electronic health record EHR) data identify patterns health care data could identify those risk developing substance misuse substance disorders those risk relapsing e.g. integration EHRs administrative data examine impact the design performance the service delivery system patient outcomes); Methods integrate analyze multiple sources health data i.e., EHR, mobile device, etc.) to Submit Response ensure consideration, responses must received July 3, 2016, should emailed vani.pariyadath@nih.gov. Respondents not receive individualized feedback. respondents encouraged sign for NIDA E-News updates http://www.drugabuse.gov/international/sign-up-e-news) receive information related Institute activities, including updates the development release the final Strategic Plan. Responses this RFI voluntary. Please not include any personally identifiable other information you not wish make public. Proprietary, classified, confidential, sensitive information should be included responses. Comments submitted be compiled discussion incorporated the NIDA Strategic Plan appropriate. Any personal identifiers personal names, email addresses, etc.) be removed responses compiled. RFI for informational planning purposes only should be construed a solicitation as obligation the part the Federal Government general, NIH, NIDA specifically. NIDA does intend make any awards based responses this RFI pay the preparation any information submitted for Government’s of such information. Inquiries Please direct inquiries to: Vani Pariyadath National Institute Drug Abuse NIDA) Telephone: 301-443-3209 Email: vani.pariyadath@nih.gov

data science, big data, informatics, machine learning
Request for Information (RFI): Making Data Usable--A Framework for Community-Based Data and Metadata Standards Efforts for NIH-relevant Research

NOT-ES-15-002

NIEHS

Nov 06 2014

N/A

Request Information RFI): Making Data Usable--A Framework Community-Based Data Metadata Standards Efforts NIH-relevant Research Notice Number: NOT-ES-15-002 Key Dates Release Date: November 5, 2014 Response Date: December 5, 2014 Related Announcements None Issued National Institute Environmental Health Sciences NIEHS) National Cancer Institute NCI) National Institute Aging NIA) National Institute Allergy Infectious Diseases NIAID) 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 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) Office Strategic Coordination Common Fund) Purpose mission the NIH Big Data Knowledge BD2K) initiative to enable biomedical scientists capitalize fully the Big Data being generated those research communities. BD2K aims develop new approaches, standards, methods, tools, software, competencies will enhance use biomedical Big Data1 supporting research, implementation, training data science other relevant fields. addressing goal, important aspect to biomedical research data resources maximally shareable reusable. this reason, BD2K formulating approaches encourage development facilitate use data-related including metadata) standards broadly across biomedical research community is, therefore, interested the issues involved developing community-based standards. Request Information RFI) solicits comments ideas related how community standards activities initiated, developed, disseminated, sustained any role NIH might play helping catalyze such efforts. Background Community-based data metadata standards been generated many levels across biomedical research community, small research consortia multinational enterprises facilitate comparison integration data different sources, accelerate collaboration, to enable broad sharing reuse data. Examples include grass-roots efforts such the Gene Ontology GO) more heavily organized efforts such Logical Observation Identifiers Names Codes LOINC), the Digital Imaging Communication Medicine DICOM) standard radiological image transfer. Any such effort must only address specific but, also, set common issues, latter including not necessarily limited to) definition mission scope, governance operational procedures, such processes creating, publishing maintaining standards make useful widely accepted. Different groups employed range strategies variable degrees complexity, formality documentation carry their activities support community-based standards development. opportunities value secondary uses data increasing, i.e., scientists are those originally generated data increasingly able extract new knowledge them. Researchers combine existing data sets across studies integrate different complex data types address questions unanticipated the original investigator(s). ability do is highly affected the extent quality the annotation the original data sets. evidence suggests without appropriate data metadata standards, meaningful data sharing the promise new knowledge created those data, not possible2 Thus, widespread of high quality data metadata standards, part a larger effort promote data access reuse, essential NIH to fully capitalize the explosion biomedical Big Data advancing fundamental knowledge complex human biology its translation human health. NIH recognizes are already numerous standards groups, both public private, across scientific disciplines. of have developed proven processes, infrastructure, community support methodologies. NIH interested exploring the BD2K initiative contribute the improvement policies, governance, administrative procedures, funding support community-based standards CBS) efforts develop and/or extend data and/or metadata standards, how activities relate other ongoing nascent biomedical research activities. Within context, lsquo;community’ encompasses broad range stakeholders may engaged the process data standards development use, including technical developers, librarians, science domain experts, researchers, information scientists, vendors, funders, publishers, other end users. Information Requested stakeholders an interest CBS invited provide information. response include, is limited to, membership within industry, government, academia. you choose, can categorize area expertise including that apply: Standards Efforts Data Management Clinical Science Basic Science Research Information Science e.g., biomedical informatics) Publishing Library Science Funding End-user NIH seeking information include, not limited to, following areas: Effective approaches, processes, activities could advance community-based standards landscape e.g., creating collaborative workspace an advising structure toward standards development, extension, adoption). Gaps community-based data standards relevance biomedical research, including real use-cases e.g., emerging fields technologies, research domains multiple existing data standards could benefit additional work, integration and/or reconciliation). Lessons learned existing CBS efforts, particularly examples field-tested processes infrastructure known examples failures CBS efforts. Common challenges CBS development e.g., methods community engagement building interoperability other related standards). Considerations evaluating progress milestones assess data standards development utility. Effective approaches addressing need sustain useful standards, to update existing standards a field develops. Submitting Response responses must submitted BD2K_CBS_RFI@niehs.nih.gov December 5, 2014. Please include Notice number NOT-ES-15-002 the subject line. Response this RFI voluntary. Responders free address any all the categories listed above. submitted information be reviewed the NIH staff. Submitted information be considered confidential. Responses this RFI voluntary. Please not include any proprietary, classified, confidential, sensitive information your response. NIH use information submitted response this RFI its discretion will provide comments any responder's submission. collected information be reviewed NIH staff, appear reports, may shared publicly an NIH website. Government reserves right use any non-proprietary technical information summaries the state the science, any resultant solicitation(s). NIH use information gathered this RFI inform development future funding opportunity announcements. RFI for information planning purposes only should be construed a solicitation as obligation the part the Federal Government, National Institutes Health NIH), individual NIH Institutes Centers. basis claims against U.S. Government shall arise a result a response this request information from Government’s of such information. 1 term Big Data' meant capture opportunities challenges facing biomedical researchers accessing, managing, analyzing, integrating datasets diverse data types e.g., imaging, phenotypic, molecular including various '–omics'), exposure, health, behavioral, the other types biological biomedical behavioral data] are increasingly larger, diverse, more complex, that exceed abilities currently used approaches manage analyze effectively. Big Data emanate three sources: 1) small number groups produce very large amounts data, usually part projects specifically funded produce important resources use the entire research community; 2) individual investigators produce large datasets, often empowered the of readily available new technologies; 3) even greater number sources each produce small datasets e.g. research data clinical data electronic health records) whose value be amplified aggregating integrating with data. http://bd2k.nih.gov/about_bd2k.html#sthash.IF3zQOrz.dpbs. 2 the report the Data Informatics Working Group the Advisory Committee the Director, NIH ACD), available at: http://acd.od.nih.gov/Data%20and%20Informatics%20Working%20Group%20Repor.... Inquiries Please direct inquiries to: Cindy P. Lawler, Ph.D. National Institute Environmental Health Sciences NIEHS) Telephone: 919-316-4671 Email: Lawler@niehs.nih.gov

data science, big data, informatics

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