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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Identification of Prognostic Model and Biomarkers for Cancer Stem Cell Characteristics in Glioblastoma by Network Analysis of Multi-Omics Data and Stemness Indices.
Jianyang Du,Xiuwei Yan,Shan Mi,Shan Mi,Yuan Li,Hang Ji,Hang Ji,Kuiyuan Hou,Kuiyuan Hou,Shuai Ma,Yixu Ba,Yixu Ba,Peng Zhou,Lei Chen,Rui Xie,Shaoshan Hu +15 more
TL;DR: Survival analysis and experimental data confirmed that the five hub genes could be used as markers for poor prognosis of GBM, and the results based on an in vivo xenograft model are consistent with the finding that knockdown of the hub gene inhibits the growth of GSCs in vitro.
Journal ArticleDOI
Network-Based Analysis of Fatal Comorbidities of COVID-19 and Potential Therapeutics
TL;DR: The protein-protein interaction sub-network captures the effects of viral invasion on fatal comorbidities through critical pathways, and drugs that have effects on these proteinsathways based on gene expression studies are identified.
Posted ContentDOI
Morphology and gene expression profiling provide complementary information for mapping cell state
Gregory P. Way,Gregory P. Way,Ted Natoli,Adeniyi Adeboye,Lev Litichevskiy,Andrew Yang,Xiaodong Lu,Juan C. Caicedo,Beth A. Cimini,Kyle W. Karhohs,David J. Logan,Mohammad Hossein Rohban,Maria Kost-Alimova,Kate Hartland,Michael Bornholdt,Niranj Chandrasekaran,Marzieh Haghighi,Shantanu Singh,Aravind Subramanian,Anne E. Carpenter +19 more
TL;DR: In this article, using both the L1000 and Cell Painting assays to profile gene expression and cell morphology, respectively, they perturb A549 lung cancer cells with 1,327 small molecules from the Drug Repurposing Hub across six doses.
Journal ArticleDOI
Perturbational Gene-Expression Signatures for Combinatorial Drug Discovery
Chen Tsung Huang,Chiao Hui Hsieh,Yun Hsien Chung,Yen Jen Oyang,Hsuan Cheng Huang,Hsueh Fen Juan +5 more
TL;DR: A gene-expression-based strategy for combinatorial drug screening as a way to target non-mutated genes in complex diseases is corroborated and used to predict synergistic drug pairs for cancer and experimentally confirmed two unexpected drug combinations in vitro.
Journal ArticleDOI
Up-regulation of hypoxia-inducible factor antisense as a novel approach to treat ovarian cancer
Tiangong Lu,Jianming Tang,Jianming Tang,Binita Shrestha,Blake R. Heath,Li Hong,Yu Lei,Mats Ljungman,Nouri Neamati +8 more
TL;DR: Induction of hypoxic stress responses through inhibition of gp130 represents a novel approach to design effective anticancer treatments in combination with standard-of-care chemotherapy in OC and the efficacy reported here strongly supports their clinical development.
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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