Title: Modelling of gene signal attribute reduction based on neighbourhood granulation and rough approximation

Authors: Jian Xue; Fu Liu; Jing Bai; Tao Hou

Addresses: College of Communications and Engineering, Jilin University, Changchun, 130022, China; College of Electrical and Information Engineering, Beihua University, Jilin, 132021, China ' College of Communications and Engineering, Jilin University, Changchun, China ' College of Electrical and Information Engineering, Beihua University, Jilin, 132021, China ' College of Communications and Engineering, Jilin University, Changchun, 130022, China

Abstract: The update of high-throughput sequencing technology has led to the dramatic increase in the number of sequenced meta-genomic DNA sequences. However, extracting a nearly 10,000-dimensional digital signature as a species tag will inevitably bring about tremendous computational load. Therefore, how to reduce the macro features of macro-genomic DNA, how to extract and select the subset with the best characteristics as a species tag, has become a research direction of bio-informatics. In this paper, we use neighbourhood granulation and rough approximation theory modelling to study the method of attribute reduction of meta-genomic DNA fragments and to deduce the digital features of meta-genome at the 'genus' classification. The results show that this method can be effective to screen out representative species tags and improve classification efficiency.

Keywords: meta-genomics; attribute reduction; neighbourhood rough set; species classification; K-mer frequency.

DOI: 10.1504/IJMIC.2019.097999

International Journal of Modelling, Identification and Control, 2019 Vol.31 No.2, pp.161 - 168

Received: 17 Feb 2018
Accepted: 29 Mar 2018

Published online: 26 Feb 2019 *

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