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
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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Proteomics in the pharmaceutical and biotechnology industry: a look to the next decade.
TL;DR: Pioneering technologies such as proteomics have helped fuel the biotechnology and pharmaceutical industry with the discovery of novel targets and an intricate understanding of the activity of the RA as discussed by the authors.
Posted ContentDOI
Evaluating Performance of Drug Repurposing Technologies
James Schuler,Zackary Falls,William Mangione,Matthew L. Hudson,Liana Bruggemann,Ram Samudrala +5 more
TL;DR: Understanding and using different performance evaluation metrics ensures robust cross platform comparability, enabling us to continuously strive towards optimal repurposing by decreasing time and cost of drug discovery and development.
Journal ArticleDOI
Integrated bioinformatic analysis reveals the underlying molecular mechanism of and potential drugs for pulmonary arterial hypertension.
Haoru Dong,Xiuchun Li,Mengsi Cai,Chi Zhang,Weiqi Mao,Ying Wang,Qian Xu,Mayun Chen,Liangxing Wang,Xiaoying Huang +9 more
TL;DR: Wang et al. as discussed by the authors integrated three human lung tissue datasets (GSE113439, GSE53408 and GSE117261) from GEO, and a total of 151 differentially expressed genes (DEGs) were screened, followed by KEGG and GO enrichment analyses and PPI network construction.
Journal ArticleDOI
Multi-omics data integration and network-based analysis drives a multiplex drug repurposing approach to a shortlist of candidate drugs against COVID-19.
Marios Tomazou,Marilena M. Bourdakou,Marilena M. Bourdakou,George Minadakis,Margarita Zachariou,Anastasis Oulas,Evangelos Karatzas,Eleni M Loizidou,Andrea C. Kakouri,Christiana C Christodoulou,Kyriaki Savva,Maria Zanti,Anna Onisiforou,Sotiroula Afxenti,Jan Richter,Christina Christodoulou,Theodoros Kyprianou,George Kolios,Nikolas Dietis,George M. Spyrou +19 more
TL;DR: In this paper, a network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently re-rank the identified candidate drugs was devised.
Journal ArticleDOI
Application of omics- and multi-omics-based techniques for natural product target discovery.
Hong-Wei Zhang,Chao Lv,Li-Jun Zhang,Xin Guo,Yi-Wen Shen,Dale G. Nagle,Yu-Dong Zhou,Sanhong Liu,Wei-Dong Zhang,Xin Luan +9 more
TL;DR: A review of integrative omics-based methods for natural product target discovery is presented in this paper, with a particular focus on the systematic integration of multi-omics strategies, including genomics, transcriptomics, proteomics, metabolomics and bioinformatics.
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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