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
TLDR
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.About:
This article is published in Cell.The article was published on 2017-11-30 and is currently open access. It has received 1943 citations till now.read more
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Protein structure-based gene expression signatures
Rayees Rahman,Yuguang Xiong,J. G. C. van Hasselt,Jens Hansen,Eric A. Sobie,Marc R. Birtwistle,Marc R. Birtwistle,Evren Azeloglu,Ravi Iyengar,Avner Schlessinger +9 more
TL;DR: Comprehensive analyses of data from the Genotype-Tissue Expression Project (GTEx), ARCHS4, and mRNA expression of drug effects on cardiomyocytes show that structural GES (sGES) are useful for identifying robust signatures of biological phenomena.
Posted ContentDOI
A systematic genome-wide mapping of the oncogenic risks associated with CRISPR-Cas9 editing
Sanju Sinha,Kuoyuan Cheng,Mark D.M. Leiserson,David M. Wilson,Bríd M. Ryan,Joo Sang Lee,Eytan Ruppin +6 more
TL;DR: It is found that CRISPR knockouts may select for mutated variants of the cancer drivers VHL and KRAS, comparable to that of p53.
Journal ArticleDOI
A Gene Signature Identifying CIN3 Regression and Cervical Cancer Survival
Mari K. Halle,Mari K. Halle,Ane Cecilie Munk,Birgit Engesæter,Saleha Akbari,Astri Frafjord,Erling A. Hoivik,Erling A. Hoivik,David Forsse,David Forsse,Kristine Eldevik Fasmer,Kristine Eldevik Fasmer,Kathrine Woie,Ingfrid S. Haldorsen,Ingfrid S. Haldorsen,Bjørn I. Bertelsen,Emiel A. M. Janssen,Emiel A. M. Janssen,Einar Gudslaugsson,Camilla Krakstad,Camilla Krakstad,Irene T Øvestad +21 more
TL;DR: In this article, the authors established a gene signature that may predict CIN3 regression and that may aid in selecting patients who may safely refrain from conization, and established a six-gene signature predicting cervical cancer regression with a sensitivity of 91% (AUC = 0.85).
Journal ArticleDOI
A Bioinformatics Analysis Identifies the Telomerase Inhibitor MST-312 for Treating High-STMN1-Expressing Hepatocellular Carcinoma.
Szu-Jen Wang,Pei Ming Yang +1 more
TL;DR: In this paper, the authors identified Stathmin 1 (STMN1) as a prognosis biomarker and a therapeutic target for hepatocellular carcinoma (HCC) patients.
Journal ArticleDOI
Computational Drug Repositioning and Experimental Validation of Ivermectin in Treatment of Gastric Cancer.
Hanne-Line Rabben,Hanne-Line Rabben,Gøran Andersen,Aleksandr Ianevski,Magnus K. Olsen,Denis E. Kainov,Jon Erik Grønbech,Timothy C. Wang,Duan Chen,Chun-Mei Zhao,Chun-Mei Zhao +10 more
TL;DR: In this paper, the repositioning of ivermectin in treatment of gastric cancer (GC) by computational prediction based on gene expression profiles of human and mouse model of GC and validations with in silico, in vitro and in vivo approaches was performed using connectivity map (cMap) and data/pathway mining with the Ingenuity Knowledge Base.
References
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Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
Aravind Subramanian,Pablo Tamayo,Vamsi K. Mootha,Sayan Mukherjee,Benjamin L. Ebert,Michael A. Gillette,Amanda G. Paulovich,Scott L. Pomeroy,Todd R. Golub,Eric S. Lander,Jill P. Mesirov +10 more
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TL;DR: A new technique called t-SNE that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map, a variation of Stochastic Neighbor Embedding that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map.
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TL;DR: The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data and provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-power gene expression and genomic hybridization experiments.
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BLAT—The BLAST-Like Alignment Tool
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