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Funding in, findings out

For any dataset: the NCI award that paid to create it, and the awards that got a published finding out of it afterwards.

332 of 602 datasets have at least one award resolved. 31 have awards on both sides.

Datasets with awards on both sides - awards that paid to create it awards that funded work using it

prad_su2c_2015

Metastatic Prostate Cancer (SU2C/PCF Dream Team, Cell 2015)

21 awards paid to create it · 0 awards funded work that used it

Direct evidence: the award is on the paper, or the accession is in the articleWeaker: infrastructure support, or use declared but not shownHover any card to follow its chain

Why one side of this chain is empty

  • This dataset has no accession that articles quote, so no reuse can be traced and nothing it enabled is visible.

Awards that paid to create this data

Credited on the dataset's own marker paper.

AwardProjectEvidence
K08CA115927
K08FY2005–2009$684k
Integrated Functional Genomic Analyses of Melanoma
Levi A. Garraway · DANA-FARBER CANCER INST
API
K08CA188615
K08FY2014–2017$708k
Resistance to Emerging Androgen Deprivation Therapies in Prostate Cancer
Eliezer M Van Allen · DANA-FARBER CANCER INST
API
P01CA163227
P01FY2025$3.5M
Androgen Receptor Action in Castration Resistant Prostate Cancer
Steven P. Balk, PETER S NELSON · BETH ISRAEL DEACONESS MEDICAL CENTER
API
P30CA006516
P30FY2025–2026$50.6M
Dana-Farber/Harvard Cancer Center
Benjamin Levine Ebert, JEROME RITZ · DANA-FARBER CANCER INST
API
P30CA008748
P30FY2025–2026$48.4M
Antitumor Assessment
Elisa de Stanchina, FRANCESCA M GANY · SLOAN-KETTERING INST CAN RESEARCH
API
P50CA069568
P50FY1995–2013$74.2M
SPORE in Prostate Cancer
ARUL M CHINNAIYAN, KATHLEEN A COONEY · UNIVERSITY OF MICHIGAN AT ANN ARBOR
API
P50CA090381
P50FY2002–2017$56.3M
Tissue and Pathology Core
Massimo Loda, PHILIP W KANTOFF · DANA-FARBER CANCER INST
API
P50CA092629
P50FY2025–2026$5.2M
SPORE in Prostate Cancer
Yu Chen, MICHAEL J MORRIS · SLOAN-KETTERING INST CAN RESEARCH
API
P50CA097186
P50FY2025–2026$5.1M
Developmental Research Program
RUTH D ETZIONI, Martin Edwin Gleave · FRED HUTCHINSON CANCER CENTER
API
P50CA186786
P50FY2023–2026$10.6M
Michigan Prostate SPORE 2025-2030
ARUL M CHINNAIYAN, Ganesh S Palapattu · UNIVERSITY OF MICHIGAN AT ANN ARBOR
API
R01CA085912
R01FY2000–2009$2.7M
Functional Analysis of the PTEN Tumor Suppressor Protein
Levi A. Garraway, WILLIAM R SELLERS · DANA-FARBER CANCER INST
API
R01CA116337
R01FY2006–2016$5.3M
Molecular Signatures of Lethal and Indolent Prostate Cancer
MARK A. RUBIN · WEILL MEDICAL COLL OF CORNELL UNIV
API
R01CA129435
R01FY2007–2009$1.5M
Fine mapping and characterization of the 8q24 prostate cancer risk locus
MATTHEW L FREEDMAN · DANA-FARBER CANCER INST
API
R01CA131945
R01FY2008–2018$4.0M
Molecular Link Between Metabolic Syndrome and Prostate Cancer
Massimo Loda · DANA-FARBER CANCER INST
API
R01CA136578
R01FY2009–2013$1.7M
Sex-Hormones and the TMPRSS2: ERG Fusion in Prostate Cancer Progression
Lorelei Mucci · BRIGHAM AND WOMEN'S HOSPITAL
API
R01CA155169
R01FY2012–2022$3.8M
Understanding Resistance to Next Generation Antiandrogens
CHARLES L. SAWYERS · SLOAN-KETTERING INST CAN RESEARCH
API
R01CA193837
R01FY2015–2025$4.7M
Role of ETS factors in specifying prostate luminal cell identity and androgen receptor dependence
CHARLES L. SAWYERS · SLOAN-KETTERING INST CAN RESEARCH
API
R01CA193910
R01FY2015–2019$3.1M
Defining the epigenetic landscape in human prostate cancer
MYLES A BROWN, MATTHEW L FREEDMAN · DANA-FARBER CANCER INST
API
R21CA128352
R21FY2008–2009$532k
A phase II study of IPI-504 in metastatic hormone refractory prostate cancer
William K. Oh · DANA-FARBER CANCER INST
API
T32CA009437
T32FY1996–2001$2.4M
MOLECULAR TRAINING PROGRAM IN CANCER RESEARCH - COMPETIN
LAWRENCE A LOEB · UNIVERSITY OF WASHINGTON
API
U01CA111275
U01FY2004–2015$6.8M
A Systems Biology Approach to the Development of Cancer Biomarkers
ARUL M CHINNAIYAN, MARK A. RUBIN · UNIVERSITY OF MICHIGAN AT ANN ARBOR
API

Where the links come from

NIH RePORTER maps a PMID to the awards that reported it. On a dataset’s marker paper that gives the awards which created it; on an article that used the data, the awards which funded that use.

The two sides are not measured alike. Generation is complete: a dataset has one marker paper and every award on it is resolved. Reuse is a sample - the articles using a dataset can number in the thousands, and only the few dozen strongest are retrieved and looked up. Every award shown here funded reuse; there are more that are not shown.

How far it reaches

283 datasets have an award credited with creating them, 80 with using them, and 31 both.

What is missing

No citable accession means no traceable articles; no authoritative marker paper means no attributable generation award. Absence is a gap in the record. Methods.

Start from an award instead, and see every dataset it touches.