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

89Citations
Citations of this article
104Readers
Mendeley users who have this article in their library.

This article is free to access.

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: © 2013 The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Cite

CITATION STYLE

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free