The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge
Open accessAbstract
The Cancer Genome Atlas (TCGA) is a public funded project that aims to catalogue and discover major cancer-causing genomic alterations to create a comprehensive "atlas" of cancer genomic profiles. So far, TCGA researchers have analysed large cohorts of over 30 human tumours through large-scale genome sequencing and integrated multi-dimensional analyses. Studies of individual cancer types, as well as comprehensive pan-cancer analyses have extended current knowledge of tumorigenesis. A major goal of the project was to provide publicly available datasets to help improve diagnostic methods, treatment standards, and finally to prevent cancer. This review discusses the current status of TCGA Research Network structure, purpose, and achievements.
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Cites
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RNA-Seq: a revolutionary tool for transcriptomics
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The cancer genome atlas pan-cancer analysis project
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Comprehensive molecular characterization of human colon and rectal cancer
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Comprehensive molecular characterization of gastric adenocarcinoma
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Mutational heterogeneity in cancer and the search for new cancer-associated genes
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The future of digital health with federated learning
Rieke, N., Hancox, J., Li, W., Milletarì, F., Roth, H. R., Albarqouni, S., Bakas, S., Galtier, M. N., Landman, B. A., Maier-Hein, K., et al. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-00323-1 · Cited by 4,015
Artificial intelligence in healthcare
Yu, K.-H., Beam, A. L., & Kohane, I. S. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0305-z · Cited by 2,817
Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
Malta, T. M., Sokolov, A., Gentles, A. J., Burzykowski, T., Poisson, L., Weinstein, J. N., Kamińska, B., Huelsken, J., Omberg, L., Gevaert, O., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.034 · Cited by 2,180
Self-citationArtificial intelligence in digital pathology — new tools for diagnosis and precision oncology
Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V., & Madabhushi, A. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0252-y · Cited by 1,698
Metadata
- Authors
- Tomczak, K., Czerwińska, P., & Wiznerowicz, M.
- Venue
- Współczesna Onkologia
- Publisher
- Termedia Sp. z.o.o.
- Published
- 2015
- Volume
- 1A
- Issue
- 1A
- Pages
- 68-77
- ISSN
- 1428-2526 (ISSN-L)
- OpenAlex
- W2329659234
- Cited by
- 3,492
- References
- 16
- FWCI
- 34.54
- Type
- journal article
- Language
- pl
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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