Title: A flexible approach to reconstruct the genomic spatial structure by the genetic algorithm

Authors: Yan Zhang; William Hoskins; Ruofan Xia; Xiya Xia; Jim W. Zheng; Jijun Tang

Addresses: Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29208, USA ' Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29208, USA ' Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29208, USA ' Department of Statistics, University of South Carolina, Columbia, SC, 29208, USA ' School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA ' Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29208, USA; Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjing, 300072, China

Abstract: The 3D structures of the chromosomes play fundamental roles in essential cellular functions, e.g., gene regulation, gene expression, evolution. HiC technique provides the interaction density between loci on chromosomes. Several approaches have been developed to reconstruct the 3D model of the chromosomes from HiC data. However, all of the approaches are based on a particular mathematical model and lack of flexibility for new development. We introduce a novel approach using the genetic algorithm. Our approach is flexible to accept any mathematical models to build a 3D chromosomal structure. Also, our approach outperforms current techniques in accuracy.

Keywords: genome; spatial structure; genetic algorithm; HiC.

DOI: 10.1504/IJCBDD.2018.090825

International Journal of Computational Biology and Drug Design, 2018 Vol.11 No.1/2, pp.39 - 51

Received: 17 Mar 2017
Accepted: 01 May 2017
Published online: 28 Mar 2018 *

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