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
Reads0
Chats0
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
More filters
Journal ArticleDOI
A molecular quantitative trait locus map for osteoarthritis
Julia Steinberg,Lorraine Southam,Theodoros I. Roumeliotis,Theodoros I. Roumeliotis,M.J. Clark,Raveen L Jayasuriya,D Swift,Karan M. Shah,Natalie C. Butterfield,Roger A. Brooks,Andrew McCaskie,J. H. Duncan Bassett,Graham R. Williams,Jyoti S. Choudhary,Jyoti S. Choudhary,J. Mark Wilkinson,Eleftheria Zeggini,Eleftheria Zeggini +17 more
TL;DR: In this article, the authors study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease, and discover molecular trait loci in each tissue type and omics level.
Journal ArticleDOI
Drug repurposing for Alzheimer's disease based on transcriptional profiling of human iPSC-derived cortical neurons.
Gareth Williams,Ariana Gatt,Earl Clarke,Jonathan Corcoran,Patrick Doherty,David J. Chambers,Clive Ballard +6 more
TL;DR: It is hoped that the iPSC profiles will serve as a useful resource for drug repositioning within the context of neurodegenerative disease and potentially aid in generating novel multi-targeted therapeutic strategies.
Journal ArticleDOI
Relevant Applications of Generative Adversarial Networks in Drug Design and Discovery: Molecular De Novo Design, Dimensionality Reduction, and De Novo Peptide and Protein Design.
TL;DR: This review examines the latest developments for three particular arenas in drug design and discovery research using deep learning approaches, such as generative adversarial network (GAN) frameworks, and describes various GAN models to fulfill the dimension reduction task of single-cell data in the preclinical stage of the drug development pipeline.
Journal ArticleDOI
Patient-derived cell line, xenograft and organoid models in lung cancer therapy
TL;DR: Different pre-clinical lung cancer models are discussed, including established cell lines, patient-derived cell Lines, xenografts and organoids, and their relative advantages and limitations in different oncologic research applications are reviewed.
Journal ArticleDOI
An Interactive Resource to Probe Genetic Diversity and Estimated Ancestry in Cancer Cell Lines.
TL;DR: The implications of genetic ancestry and diversity of cellular models for cancer research are discussed and an interactive tool, Estimated Cell Line Ancestry (ECLA), where ancestry can be visualized with reference populations of the 1000 Genomes Project is presented.
References
More filters
Journal ArticleDOI
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.
Related Papers (5)
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Jordi Barretina,Giordano Caponigro,Nicolas Stransky,Kavitha Venkatesan,Adam A. Margolin,Adam A. Margolin,Sungjoon Kim,Christine D. Wilson,Joseph Lehar,Gregory V. Kryukov,Dmitriy Sonkin,Anupama Reddy,Manway Liu,Lauren Murray,Michael F. Berger,Michael F. Berger,John Monahan,Paula Morais,Jodi Meltzer,Adam Korejwa,Judit Jané-Valbuena,Judit Jané-Valbuena,Felipa A. Mapa,Joseph Thibault,Eva Bric-Furlong,Pichai Raman,Aaron Shipway,Ingo H. Engels,Jill Cheng,Guoying K. Yu,Jianjun Yu,Peter Aspesi,Melanie de Silva,Kalpana Jagtap,Michael D. Jones,Li Wang,Charlie Hatton,Emanuele Palescandolo,Supriya Gupta,Scott Mahan,Carrie Sougnez,Robert C. Onofrio,Ted Liefeld,Laura E. MacConaill,Wendy Winckler,Michael R. Reich,Nanxin Li,Jill P. Mesirov,Stacey Gabriel,Gad Getz,Kristin G. Ardlie,Vivien W. Chan,Vic E. Myer,Barbara L. Weber,Jeffrey A. Porter,Markus Warmuth,Peter Finan,Jennifer L. Harris,Matthew Meyerson,Matthew Meyerson,Todd R. Golub,Michael Morrissey,William R. Sellers,Robert Schlegel,Levi A. Garraway,Levi A. Garraway +65 more