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.
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
1. Awards that paid to create this data (6 of 21)
- Integrated Functional Genomic Analyses of Melanoma · Levi A. Garraway · FY2005–2009
- Resistance to Emerging Androgen Deprivation Therapies in Prostate Cancer · Eliezer M Van Allen · FY2014–2017
- Androgen Receptor Action in Castration Resistant Prostate Cancer · Steven P. Balk, PETER S NELSON · FY2025
- Dana-Farber/Harvard Cancer Center · Benjamin Levine Ebert, JEROME RITZ · FY2025–2026
- Antitumor Assessment · Elisa de Stanchina, FRANCESCA M GANY · FY2025–2026
- SPORE in Prostate Cancer · ARUL M CHINNAIYAN, KATHLEEN A COONEY · FY1995–2013
The best connected are shown.
2. The dataset
3. Articles that used it
4. Awards those articles were funded by
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.
| Award | Project | Evidence |
|---|---|---|
| K08CA115927 K08FY2005–2009$684k | Integrated Functional Genomic Analyses of Melanoma | API |
| K08CA188615 K08FY2014–2017$708k | Resistance to Emerging Androgen Deprivation Therapies in Prostate Cancer | API |
| P01CA163227 P01FY2025$3.5M | Androgen Receptor Action in Castration Resistant Prostate Cancer | API |
| P30CA006516 P30FY2025–2026$50.6M | Dana-Farber/Harvard Cancer Center | API |
| P30CA008748 P30FY2025–2026$48.4M | Antitumor Assessment | API |
| P50CA069568 P50FY1995–2013$74.2M | SPORE in Prostate Cancer | API |
| P50CA090381 P50FY2002–2017$56.3M | Tissue and Pathology Core | API |
| P50CA092629 P50FY2025–2026$5.2M | SPORE in Prostate Cancer | API |
| P50CA097186 P50FY2025–2026$5.1M | Developmental Research Program | API |
| P50CA186786 P50FY2023–2026$10.6M | Michigan Prostate SPORE 2025-2030 | API |
| R01CA085912 R01FY2000–2009$2.7M | Functional Analysis of the PTEN Tumor Suppressor Protein | API |
| R01CA116337 R01FY2006–2016$5.3M | Molecular Signatures of Lethal and Indolent Prostate Cancer | API |
| R01CA129435 R01FY2007–2009$1.5M | Fine mapping and characterization of the 8q24 prostate cancer risk locus | API |
| R01CA131945 R01FY2008–2018$4.0M | Molecular Link Between Metabolic Syndrome and Prostate Cancer | API |
| R01CA136578 R01FY2009–2013$1.7M | Sex-Hormones and the TMPRSS2: ERG Fusion in Prostate Cancer Progression | API |
| R01CA155169 R01FY2012–2022$3.8M | Understanding Resistance to Next Generation Antiandrogens | API |
| R01CA193837 R01FY2015–2025$4.7M | Role of ETS factors in specifying prostate luminal cell identity and androgen receptor dependence | API |
| R01CA193910 R01FY2015–2019$3.1M | Defining the epigenetic landscape in human prostate cancer | API |
| R21CA128352 R21FY2008–2009$532k | A phase II study of IPI-504 in metastatic hormone refractory prostate cancer | API |
| T32CA009437 T32FY1996–2001$2.4M | MOLECULAR TRAINING PROGRAM IN CANCER RESEARCH - COMPETIN | API |
| U01CA111275 U01FY2004–2015$6.8M | A Systems Biology Approach to the Development of Cancer Biomarkers | 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.