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
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DeepSide: A Deep Learning Framework for Drug Side Effect Prediction
TL;DR: A multi-modal architecture produces the best predictive performance among multi-layer perceptron-based architectures when drug chemical structure (CS), and the full set of drug perturbed gene expression profiles (GEX) are used as modalities, and it is observed that the CS is more informative than the GEX.
Journal ArticleDOI
Identification of candidate repurposable drugs to combat COVID-19 using a signature-based approach.
Sinead M. O’Donovan,Ali S Imami,Hunter M. Eby,Nicholas D. Henkel,Justin F. Creeden,Sophie Asah,Xiaolu Zhang,Xiaojun Wu,Rawan Alnafisah,R. Travis Taylor,James Reigle,James Reigle,Alexander William Thorman,Behrouz Shamsaei,Jarek Meller,Robert E. McCullumsmith +15 more
TL;DR: In this paper, a bioinformatics workflow was deployed to identify candidate drugs for the treatment of COVID-19 pandemic caused by the novel SARS-CoV-2.
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Connectivity map-based drug repositioning of bortezomib to reverse the metastatic effect of GALNT14 in lung cancer
Ok Seon Kwon,Ok Seon Kwon,Haeseung Lee,Hyeon Joon Kong,Eun Ji Kwon,Ji Eun Park,Wooin Lee,Seungmin Kang,Mirang Kim,Wankyu Kim,Hyuk-Jin Cha +10 more
TL;DR: An in silico approach based on large-scale gene expression signatures to identify drug candidates for lung cancer metastasis and identifies bortezomib (BTZ) as a potent metastatic inhibitor, bypassing the direct inhibition of the enzymatic activity of GALNT14.
Journal ArticleDOI
The clinical and biological characteristics of NUP98-KDM5A in pediatric acute myeloid leukemia.
Sanne Noort,Priscilla Wander,Todd A. Alonzo,Jenny L. Smith,Rhonda E. Ries,Robert B. Gerbing,M. Emmy M. Dolman,Franco Locatelli,Dirk Reinhardt,André Baruchel,Jan Stary,Jan J. Molenaar,Ronald W. Stam,Marry M. van den Heuvel-Eibrink,C. Michel Zwaan,Soheil Meshinchi +15 more
TL;DR: The clinical and biological characteristics of NUP98-KDM5A in pediatric acute myeloid leukemia are similar to that of a “navel-Eibrink vaccination”, which is similar to a vaccination for Gaucher’s disease.
Journal ArticleDOI
Matrix Factorization-based Technique for Drug Repurposing Predictions
TL;DR: This work presents an innovative enhancement of the NMTF method that consists of a shortest-path evaluation of drug-protein pairs using the protein-to-protein interaction network, which allows inferring novel protein targets that were never considered as drug targets before, increasing the information fed to theNMTF method.
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
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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