Scatter search applied to the inference of a development gene network

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• dc.contributor.author Abdol, Amir Masoud
• dc.contributor.author Cicin Sain, Damjan
• dc.contributor.author Kaandorp, Jaap A.
• dc.contributor.author Crombach, Anton
• dc.date.accessioned 2023-02-13T08:54:25Z
• dc.date.available 2023-02-13T08:54:25Z
• dc.date.issued 2017
• dc.description.abstract Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational costs and prohibit a wide application of current methods. Therefore, reducing computational cost and providing quick feedback at intermediate stages are desirable features for network inference. Here we propose a hybrid approach composed of two stages: exploration with scatter search and exploitation of intermediate solutions with low temperature simulated annealing. We test the approach on the well-understood process of early body plan development in flies, focusing on the gap gene network. We compare the hybrid approach to simulated annealing, a method of network inference with a proven track record. We find that scatter search performs well at exploring parameter space and that low temperature simulated annealing refines the intermediate results into excellent model fits. From this we conclude that for poorly-studied developmental systems, scatter search is a valuable tool for exploration and accelerates the elucidation of gene regulatory networks.
• dc.description.sponsorship We thank Johannes Jaeger for critical feedback and scientific advice. We thankfully acknowledge the computer resources, technical expertise and assistance provided by the Barcelona Supercomputing Center, which is part of the Red Española de Supercomputación. We thank SURFsara (www.surfsara.nl) for the support in using the Lisa Compute Cluster. The Centre for Genomic Regulation (CRG) acknowledges support from the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Severo Ochoa 2013-2017’, SEV-2012-0208. AC kindly acknowledges Fondation Bettencourt Schueller.
• dc.format.mimetype application/pdf
• dc.identifier.citation Abdol AM, Cicin-Sain D, Kaandorp JA, Crombach A. Scatter search applied to the inference of a development gene network. Computation. 2017 Jun;5(2):22. DOI: 10.3390/computation5020022
• dc.identifier.doi http://dx.doi.org/10.3390/computation5020022
• dc.identifier.issn 2079-3197
• dc.identifier.uri http://hdl.handle.net/10230/55731
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Computation. 2017 Jun;5(2):22
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/SEV-2012-0208
• dc.rights © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Network inference
• dc.subject.keyword Scatter search
• dc.subject.keyword Parallel simulated annealing
• dc.subject.keyword Gap gene network
• dc.subject.keyword D. melanogaster
• dc.title Scatter search applied to the inference of a development gene network
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion