| An in silico target identification using Boolean network attractors: Avoiding pathological phenotypes. | |
MedLine Citation:
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PMID: 25433558 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Target identification aims at identifying biomolecules whose function should be therapeutically altered to cure the considered pathology. An algorithm for in silico target identification using Boolean network attractors is proposed. It assumes that attractors correspond to phenotypes produced by the modeled biological network. It identifies target combinations which allow disturbed networks to avoid attractors associated with pathological phenotypes. The algorithm is tested on a Boolean model of the mammalian cell cycle and its applications are illustrated on a Boolean model of Fanconi anemia. Results show that the algorithm returns target combinations able to remove attractors associated with pathological phenotypes and then succeeds in performing the proposed in silico target identification. However, as with any in silico evidence, there is a bridge to cross between theory and practice. Nevertheless, it is expected that the algorithm is of interest for target identification. |
Authors:
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Arnaud Poret; Jean-Pierre Boissel |
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Publication Detail:
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Type: Journal Article Date: 2014-11-11 |
Journal Detail:
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Title: Comptes rendus biologies Volume: 337 ISSN: 1768-3238 ISO Abbreviation: C. R. Biol. Publication Date: 2014 Dec |
Date Detail:
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Created Date: 2014-12-01 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101140040 Medline TA: C R Biol Country: France |
Other Details:
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Languages: eng Pagination: 661-78 Citation Subset: IM |
Copyright Information:
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Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved. |
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