Novel sparse Bayesian feature selection methods for microarray analysis and QSAR variable selection

被引：0
|
作者：
Winkler, David [1 ]
Burden, Frank [1 ]
Halley, Julianne [1 ]
机构：
[1] CSIRO Mol & Hlth Technol, Clayton, Vic, Australia
来源：
DRUGS OF THE FUTURE | 2007年 / 32卷
关键词：
D O I：
暂无
中图分类号：
R9 [药学];
学科分类号：
1007 ;
摘要：
引用
收藏
页码：26 / 26
页数：1
相关论文
共 50 条
  • [11] Optimized Ranking and Selection Methods for Feature Selection with Application in Microarray Experiments
    Cui, Xinping
    Zhao, Haibing
    Wilson, Jason
    [J]. JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 2010, 20 (02) : 223 - 239
  • [12] Novel descriptor selection methods with sensitivity analysis for QSAR.
    Embrechts, MJ
    Breneman, CM
    Bennett, K
    Arciniegas, F
    [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2001, 222 : U415 - U415
  • [13] Bayesian variable selection for globally sparse probabilistic PCA
    Bouveyron, Charles
    Latouche, Pierre
    Mattei, Pierre-Alexandre
    [J]. ELECTRONIC JOURNAL OF STATISTICS, 2018, 12 (02): : 3036 - 3070
  • [14] Comparison of Feature Selection Methods for Cross-Laboratory Microarray Analysis
    Liu, Hsi-Che
    Peng, Pei-Chen
    Hsieh, Tzung-Chien
    Yeh, Ting-Chi
    Lin, Chih-Jen
    Chen, Chien-Yu
    Hou, Jen-Yin
    Shih, Lee-Yung
    Liang, Der-Cherng
    [J]. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2013, 10 (03) : 593 - 604
  • [15] Comparative study of feature selection methods on microarray data
    Miyamoto, T
    Uchimura, S
    Hamamoto, Y
    Iizuka, N
    Oka, M
    Yamada-Okabe, H
    [J]. IEEE EMBS APBME 2003, 2003, : 82 - 83
  • [16] A review of microarray datasets and applied feature selection methods
    Bolon-Canedo, V.
    Sanchez-Marono, N.
    Alonso-Betanzos, A.
    Benitez, J. M.
    Herrera, F.
    [J]. INFORMATION SCIENCES, 2014, 282 : 111 - 135
  • [17] Improved Microarray Data Analysis using Feature Selection Methods with Machine Learning Methods
    Sun, Jing
    Passi, Kalpdrum
    Jain, Chakresh Kumar
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2016, : 1527 - 1534
  • [18] A sparse Bayesian approach for joint feature selection and classifier learning
    Àgata Lapedriza
    Santi Seguí
    David Masip
    Jordi Vitrià
    [J]. Pattern Analysis and Applications, 2008, 11 : 299 - 308
  • [19] A sparse Bayesian approach for joint feature selection and classifier learning
    Lapedriza, Agata
    Segui, Santi
    Masip, David
    Vitria, Jordi
    [J]. PATTERN ANALYSIS AND APPLICATIONS, 2008, 11 (3-4) : 299 - 308
  • [20] MaskedPainter: Feature selection for microarray data analysis
    Apiletti, Daniele
    Baralis, Elena
    Bruno, Giulia
    Fiori, Alessandro
    [J]. INTELLIGENT DATA ANALYSIS, 2012, 16 (04) : 717 - 737
12345