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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Massively multiplex chemical transcriptomics at single-cell resolution
Sanjay Srivatsan,José L. McFaline-Figueroa,Vijay Ramani,Vijay Ramani,Lauren M. Saunders,Junyue Cao,Jonathan S. Packer,Hannah A. Pliner,Dana Jackson,Riza M. Daza,Lena Christiansen,Fan Zhang,Frank J. Steemers,Jay Shendure,Cole Trapnell +14 more
TL;DR: The results with histone deacetylase inhibitors support the view that chromatin acts as an important reservoir of acetate in cancer cells, and reveal substantial intercellular heterogeneity in response to specific compounds, commonalities inresponse to families of compounds, and insight into differential properties within families.
Journal ArticleDOI
Chemical probes and drug leads from advances in synthetic planning and methodology.
TL;DR: This article focuses on strategies such as diversity-oriented synthesis that aim to explore novel areas of chemical space efficiently by populating small-molecule libraries with compounds containing structural features that are typically under-represented in commercially available screening collections.
Journal ArticleDOI
Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients.
Anna C. Aschenbrenner,Maria Mouktaroudi,Benjamin Krämer,Marie Oestreich,Nikolaos Antonakos,Melanie Nuesch-Germano,Konstantina Gkizeli,Lorenzo Bonaguro,Nico Reusch,Kevin Baßler,Maria Saridaki,Rainer Knoll,Tal Pecht,Theodore S. Kapellos,Sarandia Doulou,Charlotte Kröger,Miriam Herbert,Lisa Holsten,Arik Horne,Ioanna D. Gemünd,Nikoletta Rovina,Shobhit Agrawal,Kilian Dahm,Martina van Uelft,Anna Drews,Lena Lenkeit,Niklas Bruse,Jelle Gerretsen,Jannik Gierlich,Matthias Becker,Kristian Händler,Michael Kraut,Heidi Theis,Simachew Mengiste,Elena De Domenico,Jonas Schulte-Schrepping,Lea Seep,Jan Raabe,Christoph Hoffmeister,Michael ToVinh,Verena Keitel,Gereon Rieke,Valentina Talevi,Dirk Skowasch,N. Ahmad Aziz,N. Ahmad Aziz,Peter Pickkers,Frank L. van de Veerdonk,Mihai G. Netea,Mihai G. Netea,Joachim L. Schultze,Joachim L. Schultze,Matthijs Kox,Monique M.B. Breteler,Monique M.B. Breteler,Jacob Nattermann,Antonia Koutsoukou,Evangelos J. Giamarellos-Bourboulis,Thomas Ulas +58 more
TL;DR: This article performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis.
Journal ArticleDOI
A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions
TL;DR: This study reviews recent advancements in the field of computational drug repositioning and summarizes computational approaches that are extensively used in drug Repositioning studies.
Journal ArticleDOI
Image-based profiling for drug discovery: due for a machine-learning upgrade?
TL;DR: How the application of machine learning is renewing interest in image-based profiling for all aspects of the drug discovery process, from understanding disease mechanisms to predicting a drug’s activity or mechanism of action is discussed.
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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