Project description:A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity These data support the publication titled "A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity" Copyright (c) 2005 by Iconix Pharmaceuticals, Inc. Guidelines for commercial use: http://www.iconixbiosciences.com/guidelineCommUse.pdf replicated drug treatments with controls
Project description:A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity These data support the publication titled "A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity" Copyright (c) 2005 by Iconix Pharmaceuticals, Inc. Guidelines for commercial use: http://www.iconixbiosciences.com/guidelineCommUse.pdf Keywords: time course
Project description:Drug Toxicity Signature Generation Center (DToxS) at the Icahn School of Medicine at Mount Sinai is an integral part of the NIH Library of Integrated Network-Based Cellular Signatures (LINCS) program. A key aim of DToxS is to generate both proteomic and transcriptomic signatures that cab predict adverse effects, especially cardiotoxicity, of drugs approved by the Food and Drug Administration. Towards this goal, high throughput shot-gun proteomics experiments (308 cell line/drug combinations + 64 HeLa control lysates + 9 auxiliary treatment samples) have been conducted at the Center for Advanced Proteomics Research at Rutgers-New Jersey Medical School. The integrated proteomic and transcriptomic signatures have been used for computational network analysis to identify cellular signatures of cardiotoxicity that may predict drug-induced toxicity and possible mitigation of such toxicities by mixing different drugs. Both raw and processed proteomics data have been carefully controlled for quality and have been made publicly available via the PRoteomics IDEntifications (PRIDE) database. As such, this broad drug-stimulated proteomic dataset is valuable for the prediction drug toxicities and their mitigation.
Project description:The Library of Integrated Cellular Signatures (LINCS) is an NIH program which funds the generation of perturbational profiles across multiple cell and perturbation types, as well as read-outs, at a massive scale. The LINCS PCCSE uses two high-throughput liquid chromatography-mass spectrometry (LCMS) assays to study the proteomic changes induced by drug and genetic perturbations. P100 monitors ~100 phosphorylated peptides from cellular proteins that serve as a reduced representation of the phosphoproteome. GCP monitors ~60 modified peptides from histones (e.g., methylated, acetylated, and combinations thereof) encompassing nearly every well-studied post-translational modification on the core nucleosomal histone proteins. Closely complementing these assays is the L1000 high-throughput gene-expression assay. The files available here contain P100, GCP, and L1000 data for 90 small-molecule perturbations in six cell lines (five cancer cell lines and a neurodevelopmental cell model). These data were generated under the auspices of the NIH LINCS Program (www.lincsproject.org). Note: Related GEO projects include a large corpus of additional L1000 data, available at GSE92742. The Platform for the L1000 data is GPL20573: Broad Institute Human L1000 epsilon http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the Connectivity Map support team at: clue@broadinstitute.org
Project description:The Library of Integrated Cellular Signatures (LINCS) is an NIH program which funds the generation of perturbational profiles across multiple cell and perturbation types, as well as read-outs, at a massive scale. The LINCS Center for Transcriptomics at the Broad Institute uses the L1000 high-throughput gene-expression assay to build a Connectivity Map which seeks to enable the discovery of functional connections between drugs, genes and diseases through analysis of patterns induced by common gene-expression changes. These files represent L1000 data generated during the LINCS Pilot Phase (2012-2015), as well as profiles generated for more specific purposes, such as assay development and validation projects or testing custom compounds or non-standard cell lines (not part of the core LINCS cell lines). Note: Related GEO projects include (a) Additional L1000 and RNA-Seq data used to validate the assay and improve the inference model, available at GSE92743 (b) The LINCS “production phase” (also termed Phase II, 2015-2020) which is generating an additional cohort of L1000 data, available at GSE70138. The Platform is GPL20573: Broad Institute Human L1000 epsilon https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: clue@broadinstitute.org
Project description:The Library of Integrated Cellular Signatures (LINCS) is an NIH program which funds the generation of perturbational profiles across multiple cell and perturbation types, as well as read-outs, at a massive scale. The LINCS Center for Transcriptomics at the Broad Institute uses the L1000 high-throughput gene-expression assay to build a Connectivity Map which seeks to enable the discovery of functional connections between drugs, genes and diseases through analysis of patterns induced by common gene-expression changes. The platform is GPL20573: Broad Institute Human L1000 epsilon http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: clue@broadinstitute.org