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Liu, X. ; Vogt, I. ; Haque, T. ; Campillos, M.

HitPick: A web server for hit identification and target prediction of chemical screenings.

Bioinformatics 29, 1910-1912 (2013)
DOI PMC
Open Access Green as soon as Postprint is submitted to ZB.
MOTIVATION: High-throughput phenotypic assays reveal information about the molecules that modulate biological processes such as a disease phenotype and a signaling pathway. In these assays, the identification of hits along with their molecular targets is critical to understand the chemical activities modulating the biological system. Here, we present HitPick, a web server for identification of hits in high-throughput chemical screenings and prediction of their molecular targets. HitPick applies the B-score method for hit identification and a newly developed approach combining 1-Nearest-Neighbour (1NN) similarity searching and Laplacian-modified naïve Bayesian target models to predict targets of identified hits. The performance of the HitPick web server is presented and discussed. AVAILABILITY: The server can be accessed at http://mips.helmholtz-muenchen.de/proj/hitpick CONTACT: monica.campillos@helmholtz-muenchen.de.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Similarity ; Resource ; Database
ISSN (print) / ISBN 1367-4803
e-ISSN 1367-4811
Journal Bioinformatics
Quellenangaben Volume: 29, Issue: 15, Pages: 1910-1912 Article Number: , Supplement: ,
Publisher Oxford University Press
Publishing Place Oxford
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Bioinformatics and Systems Biology (IBIS)