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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Celastrol: A lead compound that inhibits SARS‐CoV‐2 replication, the activity of viral and human cysteine proteases, and virus‐induced IL‐6 secretion
Carlos Alessandro Fuzo,Ronaldo B. Martins,Thais Fernanda de Campos Fraga-Silva,Martin K. Amstalden,Thais Canassa De Leo,Juliano de Paula Souza,Thais Martins de Lima,Lúcia Helena Faccioli,Debora N. Okamoto,Maria A. Juliano,Suzelei C. França,Luiz Juliano,Vânia Luiza Deperon Bonato,Eurico Arruda,Marcelo Dias-Baruffi +14 more
TL;DR: Celastrol is a promising lead compound to develop new drug candidates to face COVID‐19 due to its ability to suppress SARS‐CoV‐2 replication and IL‐6 production in infected cells.
Journal ArticleDOI
DeepSide: A Deep Learning Approach for Drug Side Effect Prediction
TL;DR: Uner et al. as mentioned in this paper used a convolutional neural network-based model to predict side effect-drug pairs that are reported in the literature but was missing in the ground truth side effect dataset.
Journal ArticleDOI
Detecting fabrication in large-scale molecular omics data.
Michael Bradshaw,Samuel H. Payne +1 more
TL;DR: The authors used machine learning to detect fraud in large-scale omic experiments using gene copy-number data as input, using machine learning models correctly predicted fraud with 58-100% accuracy.
Posted ContentDOI
Generating hard-to-obtain information from easy-to-obtain information: applications in drug discovery and clinical inference
Matthew Amodio,Dennis Shung,Daniel B. Burkhardt,Patrick Wong,Michael Simonov,Yu Yamamoto,David van Dijk,Francis P. Wilson,Akiko Iwasaki,Akiko Iwasaki,Smita Krishnaswamy +10 more
TL;DR: It is demonstrated that the conditional GAN model known as Feature-Mapping GAN (FMGAN), the results of expensive experiments can be predicted, saving on the costs of actually performing the experiment, and that FMGAN can accurately predict the HI, with heterogeneity in cases of distributions of HI from EI.
Journal ArticleDOI
A mitophagy-related gene signature associated with prognosis and immune microenvironment in colorectal cancer
TL;DR: Wang et al. as discussed by the authors used univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analysis to establish a prognostic signature using mitophagy related genes, which can be utilized not only as an independent predictive biomarker but also as a tool for tailoring personalizing treatment for CRC patients.
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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