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_p1000
Prostate Adenocarcinoma (MSK/DFCI, Nature Genetics 2018)
8 awards paid to create it · 0 awards funded work that used it
1. Awards that paid to create this data (6 of 8)
- Resistance to Emerging Androgen Deprivation Therapies in Prostate Cancer · Eliezer M Van Allen · FY2014–2017
- Antitumor Assessment · Elisa de Stanchina, FRANCESCA M GANY · FY2025–2026
- Tissue and Pathology Core · Massimo Loda, PHILIP W KANTOFF · FY2002–2017
- SPORE in Prostate Cancer · Yu Chen, MICHAEL J MORRIS · FY2025–2026
- Developmental Research Program · RUTH D ETZIONI, Martin Edwin Gleave · FY2025–2026
- Understanding Resistance to Next Generation Antiandrogens · CHARLES L. SAWYERS · FY2012–2022
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 |
|---|---|---|
| K08CA188615 K08FY2014–2017$708k | Resistance to Emerging Androgen Deprivation Therapies in Prostate Cancer | API |
| P30CA008748 P30FY2025–2026$48.4M | Antitumor Assessment | 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 |
| 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 |
| U54CA224079 U54FY2017–2021$13.6M | Project 2: Reversing resistance caused by lineage plasticity through epigenetic therapy | 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.