A preference-based multi-objective evolutionary strategy for Ab initio prediction of proteins

Zhenyu Song, Yajiao Tang, Xingqian Chen, Shuangbao Song, Shuangyu Song, Shangce Gao

研究成果: 書籍の章/レポート/会議録会議への寄与査読

4 被引用数 (Scopus)

抄録

Predicting the three-dimensional structure of a protein from its amino acid sequence is an important issue in the field of computational biology and bioinformatics. It remains as an unsolved problem and attract enormous researchers' interests. Different from most conventional methods, we model the protein structure prediction (PSP) problem as a multi-objective optimization problem. A three-objective energy function based on three physical terms is designed to evaluate a protein conformation. A multi-objective evolutionary strategy algorithm coupled with preference information is proposed in this study. The preference information is used in the survival criteria, focusing on the exploration of search process. The experimental results based on five proteins in PDB library demonstrate the effectiveness of proposed method. The analysis of Pareto fronts indicates that the preference information can make solutions diverse in genotypic space. Thus, the proposed method gives a new perspective for solving PSP problems.

本文言語英語
ホスト出版物のタイトルProceedings of 2017 International Conference on Progress in Informatics and Computing, PIC 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ7-12
ページ数6
ISBN(電子版)9781538619773
DOI
出版ステータス出版済み - 2017
イベント5th International Conference on Progress in Informatics and Computing, PIC 2017 - Nanjing, 中国
継続期間: 2017/12/152017/12/17

出版物シリーズ

名前Proceedings of 2017 International Conference on Progress in Informatics and Computing, PIC 2017

学会

学会5th International Conference on Progress in Informatics and Computing, PIC 2017
国/地域中国
CityNanjing
Period2017/12/152017/12/17

ASJC Scopus 主題領域

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • 情報システム
  • 信号処理

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