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Gad Getz

Researcher at Broad Institute

Publications -  627
Citations -  309042

Gad Getz is an academic researcher from Broad Institute. The author has contributed to research in topics: Cancer & Biology. The author has an hindex of 189, co-authored 520 publications receiving 247560 citations. Previous affiliations of Gad Getz include University of Colorado Denver & University of California, San Diego.

Papers
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Proceedings ArticleDOI

Abstract 3806: Progressive biallelic loss of TP53 is associated with progression of pleuropulmonary blastoma initiated by germline loss and somatic mutation of DICER1.

TL;DR: Pugh et al. as discussed by the authors found that compound DICER1 loss appears to be initiating and synergistic with incremental loss of TP53 and acquisition of additional driver mutations, which is consistent with the progressive nature of pleuropulmonary blastoma.
Patent

Compositions and methods for diagnosing, evaluating and treating cancer by means of the dna methylation status

TL;DR: In this article, a method for determining a cancer treatment prognosis for a subject in need thereof by evaluating epigenetic and genetic changes within a tumor sample from the subject, in addition, the present invention provides methods of screening test agents to identify agents that decrease tumor cell plasticity.
Proceedings ArticleDOI

Abstract 5060: Identification of somatic retrotransposon insertions across cancer types using RetroSeq

TL;DR: Using RetroSeq, a computational framework to identify novel retrotransposon insertions in paired-end sequencing data and provide evidence for the reactivation of retroTransposons in cancer, a broad range of novel retro transposon insertion events specific to each tumor are found.
Posted ContentDOI

PANOPLY: A cloud-based platform for automated and reproducible proteogenomic data analysis

TL;DR: Proteogenomics involves the integrative analysis of genomic, transcriptomic, proteomic and post-translational modification data produced by next-generation sequencing and mass spectrometry-based proteomics, and PANOPLY—a cloud-based platform for automated and reproducible proteogenomic data analysis is developed.