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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Comprehensive Integration of Genome-Wide Association and Gene Expression Studies Reveals Novel Gene Signatures and Potential Therapeutic Targets for Helicobacter pylori-Induced Gastric Disease
TL;DR: In this article, a computational biology approach, harnessing genome-wide association and gene expression studies to identify genes and pathways determining disease development, was used to define a 55-gene signature that is stably deregulated in disease conditions.
Journal ArticleDOI
L1000 Connectivity Map interrogation identifies candidate drugs for repurposing as SARS-CoV-2 antiviral therapies
Wezi Sendama,Wezi Sendama +1 more
TL;DR: Searching the L1000 Connectivity Map for modulators of a protease that facilitates coronavirus infection identifies plausible candidate drugs for repurposing as antiviral agents against SARS-CoV-2 following further investigation.
Journal ArticleDOI
Mapping brain gene coexpression in daytime transcriptomes unveils diurnal molecular networks and deciphers perturbation gene signatures
Nan Wang,Peter Langfelder,Matthew Stricos,Lalini Ramanathan,Jeffrey B. Richman,Raymond Vaca,Mary Plascencia,Xiaofeng Gu,Shasha Zhang,T. Katherine Tamai,Liguo Zhang,Fuying Gao,Koliane Ouk,Xiang Lu,Leonid V. Ivanov,Thomas F. Vogt,Q. Richard Lu,A. Jennifer Morton,Christopher S. Colwell,Jeffrey S. Aaronson,Jim Rosinski,Steve Horvath,X. William Yang +22 more
TL;DR: In this article , a large-scale transcriptomic study using 508 wild-type mouse striatal tissue samples dissected exclusively in the afternoons was conducted to define 38 highly reproducible gene coexpression modules, including 13 and 11 modules enriched in cell-type and molecular complex markers, respectively.
Journal ArticleDOI
A Qualitative Modeling Approach for Whole Genome Prediction Using High-Throughput Toxicogenomics Data and Pathway-Based Validation.
Saad Haider,Michael B. Black,Bethany Parks,Briana Foley,Barbara A. Wetmore,Melvin E. Andersen,Rebecca A. Clewell,Kamel Mansouri,Patrick D. McMullen +8 more
TL;DR: The ability of these predictive algorithms to predict pathway level responses is a positive step toward incorporating mode of action (MOA) analysis into the high throughput prioritization and testing of the large number of chemicals in need of safety evaluation.
Posted ContentDOI
PerturbNet predicts single-cell responses to unseen chemical and genetic perturbations
Hengshi Yu,Joshua D. Welch +1 more
TL;DR: This work presents PerturbNet, a deep generative model for predicting the distribution of cell states induced by unseen chemical or genetic perturbations, which holds great promise for understanding perturbation responses and ultimately designing novel chemical and genetic interventions.
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.
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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.
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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.
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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.
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Adjusting batch effects in microarray expression data using empirical Bayes methods
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