D
David Peck
Researcher at Broad Institute
Publications - 16
Citations - 17551
David Peck is an academic researcher from Broad Institute. The author has contributed to research in topics: Gene expression profiling & microRNA. The author has an hindex of 11, co-authored 16 publications receiving 14880 citations. Previous affiliations of David Peck include Massachusetts Institute of Technology.
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Journal ArticleDOI
MicroRNA expression profiles classify human cancers
Jun Lu,Gad Getz,Eric A. Miska,Eric A. Miska,Ezequiel Alvarez-Saavedra,Justin Lamb,David Peck,Alejandro Sweet-Cordero,Alejandro Sweet-Cordero,Benjamin L. Ebert,Benjamin L. Ebert,Raymond H. Mak,Raymond H. Mak,Adolfo A. Ferrando,James R. Downing,Tyler Jacks,H. Robert Horvitz,H. Robert Horvitz,Todd R. Golub,Todd R. Golub,Todd R. Golub +20 more
TL;DR: A new, bead-based flow cytometric miRNA expression profiling method is used to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers, and finds the miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours.
Journal ArticleDOI
The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease
Justin Lamb,Emily D. Crawford,David Peck,Joshua W. Modell,Irene C. Blat,Matthew J. Wrobel,Jim Lerner,Jean Philippe Brunet,Aravind Subramanian,Kenneth N. Ross,Michael Reich,Haley Hieronymus,Haley Hieronymus,Guo Wei,Guo Wei,Scott A. Armstrong,Scott A. Armstrong,Stephen J. Haggarty,Stephen J. Haggarty,Paul A. Clemons,Ru Wei,Steven A. Carr,Eric S. Lander,Eric S. Lander,Todd R. Golub +24 more
TL;DR: The first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules is created, and it is demonstrated that this “Connectivity Map” resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs.
Journal ArticleDOI
A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.
Aravind Subramanian,Rajiv Narayan,Steven M. Corsello,Steven M. Corsello,David Peck,Ted Natoli,Xiaodong Lu,Joshua Gould,John F. Davis,Andrew A. Tubelli,Jacob K. Asiedu,David L. Lahr,Jodi E. Hirschman,Zihan Liu,Melanie Donahue,Bina Julian,Mariya Khan,David Wadden,Ian Smith,Daniel D. Lam,Arthur Liberzon,Courtney Toder,Mukta Bagul,Marek Orzechowski,Oana M. Enache,Federica Piccioni,Sarah A. Johnson,Nicholas J. Lyons,Alice H. Berger,Alice H. Berger,Alykhan F. Shamji,Angela N. Brooks,Angela N. Brooks,Anita Vrcic,Corey Flynn,Jacqueline Rosains,David Y. Takeda,David Y. Takeda,Roger Hu,Desiree Davison,Justin Lamb,Kristin Ardlie,Larson Hogstrom,Peyton Greenside,Nathanael S. Gray,Nathanael S. Gray,Paul A. Clemons,Serena J. Silver,Xiaoyun Wu,Wen-Ning Zhao,Wen-Ning Zhao,Willis Read-Button,Xiaohua Wu,Stephen J. Haggarty,Stephen J. Haggarty,Lucienne Ronco,Jesse S. Boehm,Stuart L. Schreiber,Stuart L. Schreiber,Stuart L. Schreiber,John G. Doench,Joshua A. Bittker,David E. Root,Bang Wong,Todd R. Golub +64 more
TL;DR: The expanded CMap is reported, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that is shown to be highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts.
Posted ContentDOI
A Next Generation Connectivity Map: L1000 Platform And The First 1,000,000 Profiles
Aravind Subramanian,Rajiv Narayan,Steven M. Corsello,David Peck,Ted Natoli,Xiaodong Lu,Joshua Gould,John F. Davis,Andrew A. Tubelli,Jacob K. Asiedu,David L. Lahr,Jodi E. Hirschman,Zihan Liu,Melanie Donahue,Bina Julian,Mariya Khan,David Wadden,Ian Smith,Daniel D. Lam,Arthur Liberzon,Courtney Toder,Mukta Bagul,Marek Orzechowski,Oana M. Enache,Federica Piccioni,Alice H. Berger,Alykhan F. Shamji,Angela N. Brooks,Anita Vrcic,Corey Flynn,Jacqueline Rosains,David Y. Takeda,Desiree Davison,Justin Lamb,Kristin Ardlie,Larson Hogstrom,Nathanael S. Gray,Paul A. Clemons,Serena J. Silver,Xiaoyun Wu,Wen-Ning Zhao,Willis Read-Button,Xiaohua Wu,Stephen J. Haggarty,Lucienne Ronco,Jesse S. Boehm,Stuart L. Schreiber,John G. Doench,Joshua A. Bittker,David E. Root,Bang Wong,Todd R. Golub +51 more
TL;DR: A new, low-cost, high throughput reduced representation expression profiling method, L1000, is shown to be highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts.
Journal ArticleDOI
Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling.
Steven M. Corsello,Steven M. Corsello,Rohith T. Nagari,Ryan Spangler,Jordan Rossen,Mustafa Kocak,Jordan Bryan,Jordan Bryan,Ranad Humeidi,David Peck,Xiaoyun Wu,Anna Tang,Vickie M. Wang,Sam Bender,Evan Lemire,Rajiv Narayan,Philip Montgomery,Uri Ben-David,Uri Ben-David,Colin W. Garvie,Yii-Der Ida Chen,Matthew G. Rees,Nicholas J. Lyons,James M. McFarland,Bang Wong,Li Wang,Nancy Dumont,Patrick O'Hearn,Eric Stefan,Eric Stefan,John G. Doench,Caitlin N. Harrington,Heidi Greulich,Matthew Meyerson,Matthew Meyerson,Francisca Vazquez,Ayshwarya Subramanian,Jennifer Roth,Joshua Bittker,Joshua Bittker,Jesse S. Boehm,Christopher C. Mader,Aviad Tsherniak,Todd R. Golub +43 more
TL;DR: An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the cell lines' molecular features.