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.
TCGA-KIRC
Kidney Renal Clear Cell Carcinoma
15 awards paid to create it · 3 awards funded work that used it
1. Awards that paid to create this data (6 of 15)
- The von Hippel-Lindau Tumor Suppressor Protein:Roles in Cancer and Oxygen Sensi… · WILLIAM G. KAELIN · FY1996–2015
- Cancer Cell Biology Training Program · CHANNING J. DER, Yuliya Pylayeva-Gupta · FY1996–2026
- T32 Urologic Oncology Research Training Grant · Brett Stewart Carver, PETER T SCARDINO · FY1999–2025
- TCGA Data Analysis Center at Berkeley · PAUL T. SPELLMAN, Terence Paul Speed · FY2009–2016
- Center for Systems Analysis of the Cancer Regulome · ILYA SHMULEVICH · FY2009–2016
- MSKCC Center for Translational Cancer Genomic Analysis · Marc Ladanyi, CHRIS SANDER · FY2009–2016
The best connected are shown.
2. The dataset
3. Articles that used it
4. Awards those articles were funded by (3)
- Antitumor Assessment · Elisa de Stanchina, FRANCESCA M GANY · FY1985–2026funded this article
- Molecular origins and evolution to treatment resistance in genitourinary cancers · Jihye Park · FY2022–2026funded this article
- Physician Scientist Training in Cancer Research · Jennifer R Brown, James A. DeCaprio · FY1985–2026funded this article
Awards that paid to create this data
Credited on the dataset's own marker paper.
| Award | Project | Evidence |
|---|---|---|
| R01CA068490 R01FY1996–2015$5.7M | The von Hippel-Lindau Tumor Suppressor Protein:Roles in Cancer and Oxygen Sensing | API |
| T32CA071341 T32FY1996–2026$5.4M | Cancer Cell Biology Training Program | API |
| T32CA082088 T32FY1999–2025$6.9M | T32 Urologic Oncology Research Training Grant | API |
| U24CA143799 U24FY2009–2016$4.9M | TCGA Data Analysis Center at Berkeley | API |
| U24CA143835 U24FY2009–2016$10.6M | Center for Systems Analysis of the Cancer Regulome | API |
| U24CA143840 U24FY2009–2016$11.5M | MSKCC Center for Translational Cancer Genomic Analysis | API |
| U24CA143843 U24FY2009–2013$9.5M | The BCM Tumor Genome Characterization Center | API |
| U24CA143845 U24FY2009–2016$16.0M | The Cancer Genome Atlas Data Analysis Center | API |
| U24CA143848 U24FY2009–2016$20.8M | Gene Expression Patterns in Human Tumors Identified Using Transcript Sequencing | API |
| U24CA143858 U24FY2009–2016$8.9M | UCSC-Buck Inst. Genome Data Analysis Center for TCGA Research Network (GDAC) | API |
| U24CA143866 U24FY2009–2015$10.9M | Cancer transcriptome characterization using massively parallel DNA sequencing | API |
| U24CA143867 U24FY2009–2016$17.0M | Genome Characterization Center (GCC) | API |
| U24CA143882 U24FY2009–2016$13.3M | The USC-JHU Cancer Epigenome Characterization Center | API |
| U24CA143883 U24FY2009–2016$10.6M | Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC) | API |
| U24CA144025 U24FY2009–2016$14.0M | Harvard Genome Characterization Center | API |
Awards that funded work using this data
1 of 10 traced articles report an NCI award.
| Award | Project | Articles it is credited on | Evidence |
|---|---|---|---|
| P30CA008748 P30FY1985–2026$717.9M | Antitumor Assessment | API | |
| R50CA265182 R50FY2022–2026$1.7M | Molecular origins and evolution to treatment resistance in genitourinary cancers | API | |
| T32CA009172 T32FY1985–2026$23.7M | Physician Scientist Training in Cancer Research | API |
Awards that maintain or redistribute this data
Resource and center grants credited on articles that used the data. Kept out of the flow above because they pay for the pipes, not for a cohort or a finding.
| Award | Project | Evidence |
|---|---|---|
| P30CA008748 P30FY1985–2026$717.9M | Antitumor Assessment | 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.