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Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer
Author(s) -
David A. Quigley,
Ha X. Dang,
Shuang G. Zhao,
Paul Lloyd,
Rahul Aggarwal,
Joshi J. Alumkal,
Adam Foye,
Vishal Kothari,
Marc D. Perry,
Adina Bailey,
Denise Playdle,
Travis J. Barnard,
Li Zhang,
Jin Zhang,
Jack Youngren,
Marcin Cieślik,
Abhijit Parolia,
Tomasz M. Beer,
George Thomas,
Kim N.,
Martin Gleave,
Nathan A. Lack,
Amina Zoubeidi,
Robert E. Reiter,
Matthew B. Rettig,
Owen N. Witte,
Charles J. Ryan,
Lawrence Fong,
Won Bae Kim,
Terence W. Friedlander,
Jonathan Chou,
Haolong Li,
Rajdeep Das,
Hui Li,
Ruhollah Moussavi-Baygi,
Hani Goodarzi,
Luke A. Gilbert,
Primo N. Lara,
Christopher P. Evans,
Theodore C. Goldstein,
Joshua M. Stuart,
Scott A. Tomlins,
Daniel E. Spratt,
R. Keira Cheetham,
Donavan T. Cheng,
Kyle KaiHow Farh,
Julian Gehring,
Jörg Hakenberg,
Arnold Liao,
Philip G. Febbo,
John Shon,
Brad Sickler,
Serafim Batzoglou,
Karen E. Knudsen,
Housheng Hansen He,
Jiaoti Huang,
Alexander W. Wyatt,
Scott M. Dehm,
Alan Ashworth,
Arul M. Chinnaiyan,
Christopher A. Maher,
Eric J. Small,
Felix Y. Feng
Publication year - 2018
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2018.10.019
Subject(s) - biology , computational biology , prostate cancer , confusion , exome sequencing , genome , exome , transcriptome , genetics , contingency table , table (database) , structural variation , cancer , bioinformatics , mutation , gene , computer science , data mining , gene expression , psychology , psychoanalysis , machine learning

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