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.
CPTAC-3
CPTAC-Brain, Head and Neck, Kidney, Lung, Pancreas, Uterus
10 awards paid to create it · 36 awards funded work that used it
1. Awards that paid to create this data (6 of 10)
- Cancer Center Administration · ALEX MACDONALD, SELWYN M VICKERS · FY1985–2026
- MICROSCALED PROTEOGENOMICS FOR CANCER CLINICAL TRIALS · Meenakshi Anurag, STEVEN A CARR · FY2017–2021
- iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC · Bing Zhang · FY2016–2020
- PNNL Proteome Characterization Center · Tao Liu, RICHARD D SMITH · FY2016–2020
- University of Michigan Proteogenomics Data Analysis Center · ARUL M CHINNAIYAN, Saravana M Dhanasekaran · FY2016–2020
- Proteogenomic Data Analysis for Cancer Systems Biology and Clinical Translation · Li Ding, David Fenyo · FY2016–2020
The best connected are shown.
2. The dataset
3. Articles that used it (6 of 10)
- Gillette et al. · Cell · 2020687 citations
- Satpathy et al. · Cell · 2021367 citations
- Geffen et al. · Cell · 2023170 citations
- Petralia et al. · Cell · 202493 citations
- Liang et al. · Cancer cell · 202382 citations
- Dou et al. · Cancer cell · 202350 citations
The best connected are shown.
4. Awards those articles were funded by (6 of 36)
- MICROSCALED PROTEOGENOMICS FOR CANCER CLINICAL TRIALS · Meenakshi Anurag, STEVEN A CARR · FY2017–2021funded 7 of these 10 articles · also paid to create this data
- iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC · Bing Zhang · FY2016–2020funded 7 of these 10 articles · also paid to create this data
- PNNL Proteome Characterization Center · Tao Liu, RICHARD D SMITH · FY2016–2020funded 7 of these 10 articles · also paid to create this data
- University of Michigan Proteogenomics Data Analysis Center · ARUL M CHINNAIYAN, Saravana M Dhanasekaran · FY2016–2020funded 7 of these 10 articles · also paid to create this data
- Integrated high throughput proteogenomic data analysis center for CPTAC · Chet Birger, GAD A GETZ · FY2016–2020funded 7 of these 10 articles · also paid to create this data
- The Comprehensive Proteome Characterization Center at Johns Hopkins: High Preci… · DANIEL Wanyui CHAN, ZHEN ZHANG · FY2016–2020funded 7 of these 10 articles · also paid to create this data
The best connected are shown.
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
Awards that paid to create this data
Credited on the dataset's own marker paper.
| Award | Project | Evidence |
|---|---|---|
| P30CA008748 P30FY1985–2026$721.2M | Cancer Center Administration | API2 |
| U01CA214125 U01FY2017–2021$7.0M | MICROSCALED PROTEOGENOMICS FOR CANCER CLINICAL TRIALS | API2 |
| U24CA210954 U24FY2016–2020$4.9M | iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC | API2 |
| U24CA210955 U24FY2016–2020$5.3M | PNNL Proteome Characterization Center | API2 |
| U24CA210967 U24FY2016–2020$4.1M | University of Michigan Proteogenomics Data Analysis Center | API2 |
| U24CA210972 U24FY2016–2020$3.3M | Proteogenomic Data Analysis for Cancer Systems Biology and Clinical Translation | API2 |
| U24CA210979 U24FY2016–2020$4.4M | Integrated high throughput proteogenomic data analysis center for CPTAC | API2 |
| U24CA210985 U24FY2016–2020$5.3M | The Comprehensive Proteome Characterization Center at Johns Hopkins: High Precision Discovery and Confirmation of Genoproteomic Targets | API2 |
| U24CA210986 U24FY2016–2020$6.4M | Center of Excellence for High Throughput Proteogenomic Characterization | API2 |
| U24CA210993 U24FY2016–2020$4.6M | Systems Biology based Proteogenomic Translator for Cancer Marker Discovery towards Precision Medicine | API2 |
Awards that funded work using this data
10 of 10 traced articles report an NCI award. 10 of these awards also paid to create the data - the same team publishing again on its own cohort, not a duplicated row.
| Award | Project | Articles it is credited on | Evidence |
|---|---|---|---|
| P30CA008748 P30FY1985–2026$721.2M | Cancer Center Administration | API2 | |
| P30CA240139 P30FY2019–2026$40.9M | Cancer Research Training and Education Coordination | API | |
| P30CA125123 P30FY2007–2026$131.6M | Baylor College of Medicine Cancer Center - Cancer Center Support Grant | API | |
| U54CA118948 U54FY2005–2026$49.1M | Outreach Core | API | |
| U24CA271037 U24FY2022–2026$4.4M | Michigan Center for Translational Cancer Proteogenomics | API | |
| P01CA206978 P01FY2016–2025$33.4M | Functional identification of drug response and resistance in Richter's Syndrome | API | |
| U01CA271402 U01FY2022–2026$5.0M | Proteogenomic Predictors of Recurrence in Non-small Cell Lung Cancer | API | |
| R33CA263705 R33FY2021$1.5M | PRIMAVO: Interactive exploration of cancer patient precision immune monitoring data in clinical trials | API | |
| R35CA197588 R35FY2016–2026$10.2M | Role of Phosphoinositides and Protein Kinases in the control of Cancer Metabolism | API | |
| U24CA270823 U24FY2022–2026$5.3M | Center of Excellence for High Throughput Proteogenomic Characterization | API | |
| P30CA072720 P30FY1997–2026$145.9M | Cancer Center Administration | API | |
| R21CA248122 R21FY2020–2021$402k | Inference of tumor growth dynamics using genomic data | API | |
| T32CA203690 T32FY2018–2022$1.0M | Translational Breast Cancer Research Training Program | API | |
| F30CA265288 F30FY2021–2025$198k | Defining and targeting the lung cancer progenitor cell niche using a high-resolution, multi-omics approach | API | |
| F30CA271622 F30FY2023–2025$102k | Deep-learning Integration of Histopathology and Proteogenomics at a Pan-cancer Level - Resubmission | API | |
| U24CA224260 U24FY2018–2023$1.5M | Knowledge Management Center for Illuminating the Druggable Genome | API | |
| U24CA264250 U24FY2022–2026$4.1M | ARCHS4: Massive Mining of Publicly Available RNA Sequencing Data | API | |
| U54CA263001 U54FY2022–2026$18.4M | NYULH Metastasis Research Network Center (NYULH MetNet Center) | API | |
| U24CA271012 U24FY2022–2026$6.6M | Center for Advanced Multi-Omic Characterization of Cancer | API | |
| U24CA271075 U24FY2022–2026$3.9M | Center for comprehensive proteogenomic data analysis | API | |
| U01CA214125 U01FY2017–2021$7.0M | MICROSCALED PROTEOGENOMICS FOR CANCER CLINICAL TRIALS | API2 | |
| U24CA210954 U24FY2016–2020$4.9M | iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC | API2 | |
| U24CA210955 U24FY2016–2020$5.3M | PNNL Proteome Characterization Center | API2 | |
| U24CA210967 U24FY2016–2020$4.1M | University of Michigan Proteogenomics Data Analysis Center | API2 | |
| U24CA210979 U24FY2016–2020$4.4M | Integrated high throughput proteogenomic data analysis center for CPTAC | API2 | |
| U24CA210985 U24FY2016–2020$5.3M | The Comprehensive Proteome Characterization Center at Johns Hopkins: High Precision Discovery and Confirmation of Genoproteomic Targets | API2 | |
| U24CA210986 U24FY2016–2020$6.4M | Center of Excellence for High Throughput Proteogenomic Characterization | API2 | |
| U24CA210993 U24FY2016–2020$4.6M | Systems Biology based Proteogenomic Translator for Cancer Marker Discovery towards Precision Medicine | API2 | |
| U01CA214114 U01FY2017–2021$8.4M | Proteogenomic studies aimed at understanding ovarian tumor responses to agents targeting the DNA damage response and translating this knowledge into clinical benefit | API | |
| U01CA214116 U01FY2017–2021$6.8M | Proteogenomic Translational Research Center for Clinical Proteomic | API | |
| U24CA271114 U24FY2022–2026$5.0M | Proteogenomic translator for cancer biomarker discovery towards precision medicine | API | |
| U24CA210972 U24FY2016–2020$3.3M | Proteogenomic Data Analysis for Cancer Systems Biology and Clinical Translation | API2 | |
| U24CA210957 U24FY2016–2020$2.2M | OHSU Center for Specialized Data Analysis as part of the GDAN | API | |
| U24CA211006 U24FY2016–2020$1.8M | Deep Discovery and Clinical Interpretation of Germline and Somatic Cancer Drivers | API | |
| P30CA046592 P30FY1988–2026$316.8M | Cancer Center Administration | API | |
| U24CA271076 U24FY2022–2026$5.0M | iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC | 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 |
|---|---|---|
| P01CA206978 P01FY2016–2025$33.4M | Functional identification of drug response and resistance in Richter's Syndrome | API |
| P30CA046592 P30FY1988–2026$316.8M | Cancer Center Administration | API |
| P30CA072720 P30FY1997–2026$145.9M | Cancer Center Administration | API |
| P30CA125123 P30FY2007–2026$131.6M | Baylor College of Medicine Cancer Center - Cancer Center Support Grant | API |
| P30CA240139 P30FY2019–2026$40.9M | Cancer Research Training and Education Coordination | API |
| U01CA214114 U01FY2017–2021$8.4M | Proteogenomic studies aimed at understanding ovarian tumor responses to agents targeting the DNA damage response and translating this knowledge into clinical benefit | API |
| U01CA214116 U01FY2017–2021$6.8M | Proteogenomic Translational Research Center for Clinical Proteomic | API |
| U01CA271402 U01FY2022–2026$5.0M | Proteogenomic Predictors of Recurrence in Non-small Cell Lung Cancer | API |
| U24CA210957 U24FY2016–2020$2.2M | OHSU Center for Specialized Data Analysis as part of the GDAN | API |
| U24CA211006 U24FY2016–2020$1.8M | Deep Discovery and Clinical Interpretation of Germline and Somatic Cancer Drivers | API |
| U24CA224260 U24FY2018–2023$1.5M | Knowledge Management Center for Illuminating the Druggable Genome | API |
| U24CA264250 U24FY2022–2026$4.1M | ARCHS4: Massive Mining of Publicly Available RNA Sequencing Data | API |
| U24CA270823 U24FY2022–2026$5.3M | Center of Excellence for High Throughput Proteogenomic Characterization | API |
| U24CA271012 U24FY2022–2026$6.6M | Center for Advanced Multi-Omic Characterization of Cancer | API |
| U24CA271037 U24FY2022–2026$4.4M | Michigan Center for Translational Cancer Proteogenomics | API |
| U24CA271075 U24FY2022–2026$3.9M | Center for comprehensive proteogenomic data analysis | API |
| U24CA271076 U24FY2022–2026$5.0M | iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC | API |
| U24CA271114 U24FY2022–2026$5.0M | Proteogenomic translator for cancer biomarker discovery towards precision medicine | API |
| U54CA118948 U54FY2005–2026$49.1M | Outreach Core | API |
| U54CA263001 U54FY2022–2026$18.4M | NYULH Metastasis Research Network Center (NYULH MetNet Center) | 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.