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Liu, X. ; Campillos, M.

Unveiling new biological relationships using shared hits of chemical screening assay pairs.

Bioinformatics 30, i579-i586 (2014)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
MOTIVATION: Although the integration and analysis of the activity of small molecules across multiple chemical screens is a common approach to determine the specificity and toxicity of hits, the suitability of these approaches to reveal novel biological information is less explored. Here, we test the hypothesis that assays sharing selective hits are biologically related. RESULTS: We annotated the biological activities (i.e. biological processes or molecular activities) measured in assays and constructed chemical hit profiles with sets of compounds differing on their selectivity level for 1640 assays of ChemBank repository. We compared the similarity of chemical hit profiles of pairs of assays with their biological relationships and observed that assay pairs sharing non-promiscuous chemical hits tend to be biologically related. A detailed analysis of a network containing assay pairs with the highest hit similarity confirmed biological meaningful relationships. Furthermore, the biological roles of predicted molecular targets of the shared hits reinforced the biological associations between assay pairs. CONTACT: monica.campillos@helmholtz-muenchen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Unfolded Protein Response; Glucocorticoid Receptor; Target Prediction; Web Server; Cancer; Resource; Pubchem; Cells; Identification; Inhibition
ISSN (print) / ISBN 1367-4803
e-ISSN 1367-4811
Zeitschrift Bioinformatics
Quellenangaben Band: 30, Heft: 17, Seiten: i579-i586 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Verlagsort Oxford
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)
German Center for Diabetes Reseach (DZD)