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
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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
Citations
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Computational biology approaches for mapping transcriptional regulatory networks.
TL;DR: In this paper, major approaches and tools to map TRNs from high-throughput data are presented, depending on the type of methods or data used to infer them, and their advantages and limitations are discussed.
Journal ArticleDOI
Systems Pharmacology Identifies an Arterial Wall Regulatory Gene Network Mediating Coronary Artery Disease Side Effects of Antiretroviral Therapy.
Itziar Frades,Ben Readhead,Letizia Amadori,Simon Koplev,Husain A. Talukdar,Heidi M. Crane,Paul K. Crane,Jason C. Kovacic,Joel T. Dudley,Chiara Giannarelli,Johan L.M. Björkegren,Johan L.M. Björkegren,Inga Peter +12 more
TL;DR: 3 commonly used ARTs were found altering the activity of AR-RGN, a regulatory gene network promoting foam cell formation and risk of CAD, by applying a novel systems pharmacology data analysis framework.
Journal ArticleDOI
Applying Computer Simulations in Battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic
Mohammad Amin Khazeei Tabari,Hooman Khoshhal,Alireza Tafazoli,Mohanna Khandan,Abouzar Bagheri +4 more
TL;DR: The results indicate promising effects of such compounds to be used in further experimental and clinical trials and summarizes the outcomes of various computer simulations data in the battle against COVID-19.
Posted ContentDOI
Dissection of multiple sclerosis genetics identifies B and CD4 T cells as driver cell subsets
Michael H. Guo,Michael H. Guo,Prashanth Sama,Brenna A. LaBarre,Hrishikesh Lokhande,John Balibalos,Ci Chu,Xiaomi Du,Pouya Kheradpour,Charles C. Kim,Taylor K. Oniskey,Thomas Snyder,Damien Z. Soghoian,Howard L. Weiner,Tanuja Chitnis,Nikolaos A. Patsopoulos +15 more
TL;DR: This study utilized chromatin accessibility data across hematopoietic cells to identify cell type-specific enrichments of MS genetic signals and found that CD4 T and B cells were independently enriched for MS genetics and further refined the driver subsets to Th17 and memory B cells, respectively.
Journal ArticleDOI
Predicting adverse drug reactions of two-drug combinations using structural and transcriptomic drug representations to train an artificial neural network.
TL;DR: This study uses the TWOSIDES database as a source of ADRs originating from two‐drug combinations to predict 243 ADRs that were induced by at least 10% of the drug pairs and predicts the occurrence of these ADRs with an average accuracy of 82% across a multifold cross‐validation.
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
TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
Journal Article
Visualizing Data using t-SNE
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.
Journal ArticleDOI
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
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.
Journal ArticleDOI
BLAT—The BLAST-Like Alignment Tool
TL;DR: How BLAT was optimized is described, which is more accurate and 500 times faster than popular existing tools for mRNA/DNA alignments and 50 times faster for protein alignments at sensitivity settings typically used when comparing vertebrate sequences.
Journal ArticleDOI
Adjusting batch effects in microarray expression data using empirical Bayes methods
TL;DR: This paper proposed parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples.
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