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HitPick: a web server for hit identification and target prediction of chemical screenings
Xueping Liu1, Ingo Vogt, Tanzeem Haque
1Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
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.
