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Scatter Search Applied to the Inference of a Development Gene Network

Computational Science Lab, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08003 Barcelona, Spain
Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
Centre for Interdisciplinary Research in Biology, College de France, CNRS, INSERM, PSL Research University, 75231 Paris, France
Author to whom correspondence should be addressed.
Academic Editors: Gennady Bocharov, Olga Solovyova and Vitaly Volpert
Computation 2017, 5(2), 22;
Received: 10 March 2017 / Revised: 19 April 2017 / Accepted: 28 April 2017 / Published: 4 May 2017
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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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. View Full-Text
Keywords: network inference; scatter search; parallel simulated annealing; gap gene network; D. melanogaster network inference; scatter search; parallel simulated annealing; gap gene network; D. melanogaster

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Abdol, A.M.; Cicin-Sain, D.; Kaandorp, J.A.; Crombach, A. Scatter Search Applied to the Inference of a Development Gene Network. Computation 2017, 5, 22.

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