Journal
BIOINFORMATICS
Volume 29, Issue 15, Pages 1910-1912Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt303
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Funding
- German Federal Ministry of Education and Research (BMBF)
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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 naive Bayesian target models to predict targets of identified hits. The performance of the HitPick web server is presented and discussed.
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