The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
The CPTAC Data Portal: A Resource for Cancer Proteomics Research
Abstract
The Clinical Proteomic Tumor Analysis Consortium (CPTAC), under the auspices of the National Cancer Institute's Office of Cancer Clinical Proteomics Research, is a comprehensive and coordinated effort to accelerate the understanding of the molecular basis of cancer through the application of proteomic technologies and workflows to clinical tumor samples with characterized genomic and transcript profiles. The consortium analyzes cancer biospecimens using mass spectrometry, identifying and quantifying the constituent proteins and characterizing each tumor sample's proteome. Mass spectrometry enables highly specific identification of proteins and their isoforms, accurate relative quantitation of protein abundance in contrasting biospecimens, and localization of post-translational protein modifications, such as phosphorylation, on a protein's sequence. The combination of proteomics, transcriptomics, and genomics data from the same clinical tumor samples provides an unprecedented opportunity for tumor proteogenomics. The CPTAC Data Portal is the centralized data repository for the dissemination of proteomic data collected by Proteome Characterization Centers (PCCs) in the consortium. The portal currently hosts 6.3 TB of data and includes proteomic investigations of breast, colorectal, and ovarian tumor tissues from The Cancer Genome Atlas (TCGA). The data collected by the consortium is made freely available to the public through the data portal.
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ProteoWizard: open source software for rapid proteomics tools development
Kessner, D., Chambers, M., Burke, R., Agus, D., & Mallick, P. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn323 · Cited by 2,024
Proteogenomic characterization of human colon and rectal cancer
CPTAC, T. N., Zhang, B., Wang, J., Wang, X., Zhu, J., Liu, Q., Shi, Z., Chambers, M. C., Zimmerman, L. J., Shaddox, K. F., et al. (2014) · Nature · doi:10.1038/nature13438 · Cited by 1,462
Addona, T. A., Abbatiello, S. E., Schilling, B., Skates, S. J., Mani, D. R., Bunk, D. M., Spiegelman, C. H., Zimmerman, L. J., Ham, A.-J. L., Keshishian, H., et al. (2009) · Nature Biotechnology · doi:10.1038/nbt.1546 · Cited by 1,037
Tabb, D. L., Vega-Montoto, L., Rudnick, P. A., Variyath, A. M., Ham, A.-J. L., Bunk, D. M., Kilpatrick, L. E., Billheimer, D. D., Blackman, R. K., Cardasis, H. L., et al. (2010) · Journal of Proteome Research · doi:10.1021/pr9006365 · Cited by 551
Reiter, L., Claassen, M., Schrimpf, S. P., Jovanovic, M., Schmidt, A., Buhmann, J. M., Hengartner, M. O., & Aebersold, R. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900317-mcp200 · Cited by 312
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Chen, R. J., Wang, J. J., Williamson, D. F. K., Chen, T. Y., Lipkova, J., Lu, M. Y., Sahai, S., & Mahmood, F. (2023) · Nature Biomedical Engineering · doi:10.1038/s41551-023-01056-8 · Cited by 750
Proteogenomic Characterization of Endometrial Carcinoma
Dou, Y., Kawaler, E. A., Cui Zhou, D., Gritsenko, M. A., Huang, C., Blumenberg, L., Karpova, A., Petyuk, V. A., Savage, S. R., Satpathy, S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.01.026 · Cited by 485
Self-citationAdvances in medical image analysis with vision Transformers: A comprehensive review
Azad, R., Kazerouni, A., Heidari, M., Aghdam, E. K., Molaei, A., Jia, Y., Jose, A., Roy, R., & Merhof, D. (2024) · Medical Image Analysis · doi:10.1016/j.media.2023.103000 · Cited by 485
Metadata
- Authors
- Edwards, N. J., Oberti, M., Thangudu, R. R., Cai, S., McGarvey, P. B., Jacob, S., Madhavan, S., & Ketchum, K. A.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2015-05-04
- Volume
- 14
- Issue
- 6
- Pages
- 2707-2713
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2329674354
- Cited by
- 558
- References
- 5
- FWCI
- 5.38
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The CPTAC Data Portal: A Resource for Cancer Proteomics Research. https://app.cochat.ai/papers/10.1021/pr501254j
- The paper
- Edwards, N. J., Oberti, M., Thangudu, R. R., Cai, S., McGarvey, P. B., Jacob, S., Madhavan, S., & Ketchum, K. A. (2015). The CPTAC Data Portal: A Resource for Cancer Proteomics Research. Journal of Proteome Research. https://doi.org/10.1021/pr501254j
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
