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: © 2013 The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
CITATION STYLE
Liu, X., Vogt, I., Haque, T., & Campillos, M. (2013). HitPick: A web server for hit identification and target prediction of chemical screenings. Bioinformatics, 29(15), 1910–1912. https://doi.org/10.1093/bioinformatics/btt303
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