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Predicting Putative Chemical Targets using Transcriptomics
Citation:
Shah, I. Predicting Putative Chemical Targets using Transcriptomics. Presented at EU ToxRisk Presentation, RTP, NC, November 01, 2018. https://doi.org/10.23645/epacomptox.7388084
Impact/Purpose:
Targeted RNA-Seq based HTTr is a promising platform for comprehensive and cost-effective evaluation of chemically induced disruption of biological processes/pathways. We have developed a standardized, scalable, and portable workflow to generate large-scale HTTr data for thousands of chemicals.
Description:
This presentation will give a stepwise evaluation of the different approaches to target prediction: 1) connectivity mapping, can be used for any profile, sensitive but not specific, 2) pathway/signature analysis, sensitive and more specific but does not identify all targets, 3) machine learning, the most accurate but not possible to evaluate all chemicals due to insufficient annotation, 4) network analysis, using transcriptomic profile with other data to infer putative targets.
URLs/Downloads:
DOI: Predicting Putative Chemical Targets using Transcriptomics
SHAH-EUTOXRISK-NOV-1-2018-V1B.PDF (PDF, NA pp, 3356.119 KB, about PDF)