顾宏

643

  • 教授     博士生导师   硕士生导师
  • 性别:男
  • 毕业院校:浙江大学
  • 学位:博士
  • 所在单位:控制科学与工程学院
  • 学科:模式识别与智能系统
  • 办公地点:创新园大厦B0715
  • 电子邮箱:guhong@dlut.edu.cn

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开通时间:2020.12.29

最后更新时间:2020.12.29

Predicting Viral Protein Subcellular Localization with Chou's Pseudo Amino Acid Composition and Imbalance-Weighted Multi-Label K-Nearest Neighbor Algorithm

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论文类型:期刊论文

发表时间:2012-11-01

发表刊物:PROTEIN AND PEPTIDE LETTERS

收录刊物:SCIE、PubMed、Scopus

卷号:19

期号:11

页面范围:1163-1169

ISSN号:0929-8665

关键字:Class-imbalance; K-nearest neighbor; multi-label learning; pseudo amino acid composition; subcellular localization

摘要:Machine learning is a kind of reliable technology for automated subcellular localization of viral proteins within a host cell or virus-infected cell. One challenge is that the viral protein samples are not only with multiple location sites, but also class-imbalanced. The imbalanced dataset often decreases the prediction performance. In order to accomplish this challenge, this paper proposes a novel approach named imbalance-weighted multi-label K-nearest neighbor to predict viral protein subcellular location with multiple sites. The experimental results by jackknife test indicate that the presented algorithm achieves a better performance than the existing methods and has great potentials in protein science.