Literature DB >> 29548799

iRSpot-PDI: Identification of recombination spots by incorporating dinucleotide property diversity information into Chou's pseudo components.

Lichao Zhang1, Liang Kong2.   

Abstract

Recombination spot identification plays an important role in revealing genome evolution and developing DNA function study. Although some computational methods have been proposed, extracting discriminatory information embedded in DNA properties has not received enough attention. The DNA properties include dinucleotide flexibility, structure and thermodynamic parameter, which are significant for genome evolution research. To explore the potential effect of DNA properties, a novel feature extraction method, called iRSpot-PDI, is proposed. A wrapper feature selection method with the best first search is used to identify the best feature set. To verify the effectiveness of the proposed method, support vector machine is employed on the obtained features. Prediction results are reported on two benchmark datasets. Compared with the recently reported methods, iRSpot-PDI achieves the highest values of individual specificity, Matthew's correlation coefficient and overall accuracy. The experimental results confirm that iRSpot-PDI is effective for accurate identification of recombination spots. The datasets can be downloaded from the following URL: http://stxy.neuq.edu.cn/info/1095/1157.htm.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Diversity function; Property matrix; Recombination hotspots; Support vector machine

Mesh:

Year:  2018        PMID: 29548799     DOI: 10.1016/j.ygeno.2018.03.003

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  4 in total

Review 1.  Some illuminating remarks on molecular genetics and genomics as well as drug development.

Authors:  Kuo-Chen Chou
Journal:  Mol Genet Genomics       Date:  2020-01-01       Impact factor: 3.291

2.  i6mA-DNCP: Computational Identification of DNA N6-Methyladenine Sites in the Rice Genome Using Optimized Dinucleotide-Based Features.

Authors:  Liang Kong; Lichao Zhang
Journal:  Genes (Basel)       Date:  2019-10-20       Impact factor: 4.096

3.  A convolution based computational approach towards DNA N6-methyladenine site identification and motif extraction in rice genome.

Authors:  Chowdhury Rafeed Rahman; Ruhul Amin; Swakkhar Shatabda; Md Sadrul Islam Toaha
Journal:  Sci Rep       Date:  2021-05-14       Impact factor: 4.379

4.  Epigenetic Marks and Variation of Sequence-Based Information Along Genomic Regions Are Predictive of Recombination Hot/Cold Spots in Saccharomyces cerevisiae.

Authors:  Guoqing Liu; Shuangjian Song; Qiguo Zhang; Biyu Dong; Yu Sun; Guojun Liu; Xiujuan Zhao
Journal:  Front Genet       Date:  2021-06-29       Impact factor: 4.599

  4 in total

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