Political abuse of Olympic sport: DeFrantz v. United States Olympic Committee
In: New York University journal of international law & politics, Band 14, S. 155-185
ISSN: 0028-7873
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In: New York University journal of international law & politics, Band 14, S. 155-185
ISSN: 0028-7873
In: Journal of the Society for Gynecologic Investigation: official publication of the Society for Gynecologic Investigation, Band 8, Heft 2, S. 104-113
ISSN: 1556-7117
In: Journal of the Society for Gynecologic Investigation: official publication of the Society for Gynecologic Investigation, Band 5, Heft 5, S. 281-285
ISSN: 1556-7117
In: Journal of the Society for Gynecologic Investigation: official publication of the Society for Gynecologic Investigation, Band 11, Heft 1, S. 51-59
ISSN: 1556-7117
In: Journal of the Society for Gynecologic Investigation: official publication of the Society for Gynecologic Investigation, Band 10, Heft 6, S. 381-387
ISSN: 1556-7117
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale.
BASE
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types.
BASE