| Literature DB >> 23716196 |
Xueping Liu1, Ingo Vogt, Tanzeem Haque, Mónica Campillos.
Abstract
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-neighbor (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.Entities:
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Year: 2013 PMID: 23716196 DOI: 10.1093/bioinformatics/btt303
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937