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

Bioinformatics 29, 1910-1912 (2013)
Verlagsversion Volltext DOI PMC
Open Access Gold
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-Neighbour (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.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Similarity ; Resource ; Database
Sprache englisch
Veröffentlichungsjahr 2013
HGF-Berichtsjahr 2013
e-ISSN 1367-4811
Zeitschrift Bioinformatics
Quellenangaben Band: 29, Heft: 15, Seiten: 1910-1912 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Verlagsort Oxford
Begutachtungsstatus Peer reviewed
POF Topic(s) 30505 - New Technologies for Biomedical Discoveries
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-551700-002
PubMed ID 23716196
Scopus ID 84880553821
Erfassungsdatum 2013-06-04