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Mark D.M. Leiserson

Researcher at University of Maryland, College Park

Publications -  72
Citations -  27829

Mark D.M. Leiserson is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Cancer & Computer science. The author has an hindex of 23, co-authored 66 publications receiving 21838 citations. Previous affiliations of Mark D.M. Leiserson include Microsoft & Brown University.

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The cancer genome atlas pan-cancer analysis project

John N. Weinstein, +379 more
- 01 Oct 2013 - 
TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.
Journal Article

The Cancer Genome Atlas Pan-Cancer analysis project

Kyle Chang, +337 more
- 01 Sep 2013 - 
TL;DR: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels as mentioned in this paper.
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Comprehensive molecular characterization of gastric adenocarcinoma

Adam J. Bass, +257 more
- 11 Sep 2014 - 
TL;DR: A comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project is described and a molecular classification dividing gastric cancer into four subtypes is proposed.
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Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia

Timothy J. Ley, +138 more
TL;DR: It is found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients and the databases from this study are widely available to serve as a foundation for further investigations of AMl pathogenesis, classification, and risk stratification.
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Mutational landscape and significance across 12 major cancer types

TL;DR: Data and analytical results for point mutations and small insertions/deletions from 3,281 tumours across 12 tumour types are presented as part of the TCGA Pan-Cancer effort, and clinical association analysis identifies genes having a significant effect on survival.