Biological pathway conducting microarray-based cancer classification

被引:0
|
作者
Zeng, Tao [1 ]
Luo, Fei [1 ]
Liu, Juan [1 ]
机构
[1] Wuhan Univ, Sch Comp, Wuhan 430072, Peoples R China
来源
PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOLS 1-4 | 2009年
关键词
GENE; PROGNOSIS; SURVIVAL;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The cancer classification is a major and important study field in the medical research, and DNA microarrays have been proved to provide useful and great information for cancer classification at molecular level, compared with traditional clinical or histopathological information. Bio-markers from microarray gene expression analysis have developed to a new approach for cancer classification but still face the problems such as: different genetic signatures for same cancer under different methods; disregards of small but consistent changes in expression; and lack of biological systematic opinion. Here, this paper proposes biological pathway conducting cancer classification based on gene expression data with pathway information in KEGG. There are experiments on four different data-sets for breast, colon, gloimas and lymphoma cancer: the accuracy of these classifications are all promoted about 10%, and even achieve 100% in LOOCV on gloimas data;the pathway conducting classifiers show more significant biological functional features than genetic bio-markers. * to whom correspondence should be addressed.
引用
收藏
页码:1577 / 1581
页数:5
相关论文
共 50 条
  • [1] A Pathway-Based Classification Method That Can Improve Microarray-Based Colorectal Cancer Diagnosis
    Wang, Hong-Qiang
    Xie, Xin-Ping
    Zheng, Chun-Hou
    BIO-INSPIRED COMPUTING AND APPLICATIONS, 2012, 6840 : 610 - +
  • [2] A Robust Gene Selection Method for Microarray-based Cancer Classification
    Wang, Xiaosheng
    Gotoh, Osamu
    CANCER INFORMATICS, 2010, 9 : 15 - 30
  • [3] Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification
    Fajila, Fathima
    Yusof, Yuhanis
    JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY-MALAYSIA, 2025, 24 (01): : 102 - 129
  • [4] Effect of normalization on microarray-based classification
    Hua, Jianping
    Balagurunathan, Yoganand
    Chen, Yidong
    Lowey, Daines
    Bittner, Michael L.
    Xiong, Zixiang
    Suh, Edward
    Dougherty, Edward R.
    2006 IEEE INTERNATIONAL WORKSHOP ON GENOMIC SIGNAL PROCESSING AND STATISTICS, 2006, : 7 - +
  • [5] Normalization Benefits Microarray-Based Classification
    Hua, Jianping
    Balagurunathan, Yoganand
    Chen, Yidong
    Lowey, James
    Bittner, Michael L.
    Xiong, Zixiang
    Suh, Edward
    Dougherty, Edward R.
    EURASIP JOURNAL ON BIOINFORMATICS AND SYSTEMS BIOLOGY, 2006, (01): : 1 - 13
  • [6] Gene Selection Using Interaction Information for Microarray-based Cancer Classification
    Nakariyakul, Songyot
    2016 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY (CIBCB), 2016,
  • [7] Small sample issues for microarray-based classification
    Dougherty, ER
    COMPARATIVE AND FUNCTIONAL GENOMICS, 2001, 2 (01): : 28 - 34
  • [8] Microarray-Based Disease Classification Using Pathway Activities with Negatively Correlated Feature Sets
    Sootanan, Pitak
    Prom-on, Santitham
    Meechai, Asawin
    Chan, Jonathan H.
    NEURAL INFORMATION PROCESSING: MODELS AND APPLICATIONS, PT II, 2010, 6444 : 250 - +
  • [9] A hybrid gene selection algorithm based on interaction information for microarray-based cancer classification
    Nakariyakul, Songyot
    PLOS ONE, 2019, 14 (02):
  • [10] The application of ant colony optimization for gene selection in microarray-based cancer classification
    Chiang, Yu-Min
    Chiang, Huei-Min
    Lin, Shang-Yi
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, : 4001 - 4006