Two-stage clustering based effective sample selection for classification of premiRNAs

被引:0
|
作者
Xuan, Ping [1 ]
Guo, Mao-zu [1 ]
Shi, Lei-lei [2 ]
Wang, Jun [1 ]
Liu, Xiao-yan [1 ]
Li, Wen-bin [3 ]
Han, Ying-peng [3 ]
机构
[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Heilongjiang, Peoples R China
[2] Univ Kent, Comp Lab, Canterbury CT2 7NF, Kent, England
[3] Northeast Agr Univ, Soybean Res Inst, Harbin 150030, Heilongjiang, Peoples R China
来源
2010 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE | 2010年
关键词
PREDICTION; MICRORNAS; FEATURES; REAL;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
To solve the class imbalance problem in classification of pre-miRNAs with ab initio method, a novel sample selection method is proposed according to the characteristics of pre-miRNAs. Real/pseudo premiRNAs are clustered based on their stem similarity and their distribution in high dimensional sample space respectively. The training samples are selected according to the sample density of each cluster. Experimental results are validated by the cross validation and other testing datasets composed of human real/pseudo pre-miRNAs. When compared with the previous study, microPred, our classifier miRNAPred is nearly 12% greater in total accuracy. Our sample selection algorithm is useful to construct more efficient classifier for classification of real premiRNAs and pseudo hairpin sequences.
引用
收藏
页码:549 / 552
页数:4
相关论文
共 50 条
  • [21] A Two-stage Text Feature Selection Algorithm for Improving Text Classification
    Ashokkumar, P.
    Shankar, Siva G.
    Srivastava, Gautam
    Maddikunta, Praveen Kumar Reddy
    Gadekallu, Thippa Reddy
    ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2021, 20 (03)
  • [22] Two-stage NER for tweets with clustering
    Liu, Xiaohua
    Zhou, Ming
    INFORMATION PROCESSING & MANAGEMENT, 2013, 49 (01) : 264 - 273
  • [23] A two-stage density clustering algorithm
    Min Wang
    Ying-Yi Zhang
    Fan Min
    Li-Ping Deng
    Lei Gao
    Soft Computing, 2020, 24 : 17797 - 17819
  • [24] A two-stage density clustering algorithm
    Wang, Min
    Zhang, Ying-Yi
    Min, Fan
    Deng, Li-Ping
    Gao, Lei
    SOFT COMPUTING, 2020, 24 (23) : 17797 - 17819
  • [25] Using two-stage approach to clustering
    Yue, Shihong
    Song, Kai
    Li, Yi
    2006 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1-6, 2006, : 488 - +
  • [26] Unsupervised Pixel Classification in Satellite Imagery: A Two-stage Fuzzy Clustering Approach
    Mukhopadhyay, Anirban
    Maulik, Ujjwal
    FUNDAMENTA INFORMATICAE, 2008, 86 (04) : 411 - 428
  • [27] Two-stage clustering algorithm based on evolution and propagation patterns
    Peng Li
    Haibin Xie
    Applied Intelligence, 2022, 52 : 11555 - 11568
  • [28] Chinese Person Name Disambiguation Based on Two-Stage Clustering
    Zhou, Jie
    Li, Bicheng
    Tang, Yongwang
    JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2016, 20 (05) : 755 - 764
  • [29] A Method of Two-Stage Clustering Based on Cluster Validity Measures
    Ozaki, Ryo
    Hamasuna, Yukihiro
    Endo, Yasunori
    2016 JOINT 8TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 17TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS), 2016, : 410 - 415
  • [30] Two-stage clustering algorithm based on evolution and propagation patterns
    Li, Peng
    Xie, Haibin
    APPLIED INTELLIGENCE, 2022, 52 (10) : 11555 - 11568