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Liu, X. ; Vogt, I. ; Haque, T. ; Campillos, M.

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

Bioinformatics 29, 1910-1912 (2013)
DOI PMC
Open Access Gold möglich sobald Verlagsversion bei der ZB eingereicht worden ist.
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
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
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)