Document Detail


Biological network inference for drug discovery.
MedLine Citation:
PMID:  23147668     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
A better understanding of the pathophysiology should help deliver drugs whose targets are involved in the causative processes underlying the disease. Biological network inference uses computational methods for deducing from high-throughput experimental data, the topology and the causal structure of the interactions among the drugs and their targets. Therefore, biological network inference can support and contribute to the experimental identification of both gene and protein networks causing a disease as well as the biochemical networks of drugs metabolism and mechanisms of action. The resulting high-level networks serve as a foundational basis for more detailed mechanistic models and are increasingly used in drug discovery by pharmaceutical and biotechnology companies. We review and compare recent computational technologies for network inference applied to drug discovery.
Authors:
Paola Lecca; Corrado Priami
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-9
Journal Detail:
Title:  Drug discovery today     Volume:  -     ISSN:  1878-5832     ISO Abbreviation:  Drug Discov. Today     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-13     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9604391     Medline TA:  Drug Discov Today     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012. Published by Elsevier Ltd.
Affiliation:
The Microsoft Research, University of Trento, Centre for Computational and Systems Biology, Piazza Manifattura 1 - 38068 Rovereto, Italy. Electronic address: lecca@cosbi.eu.
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