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  • 标题:The non-negative matrix factorization toolbox for biological data mining
  • 本地全文:下载
  • 作者:Yifeng Li ; Alioune Ngom
  • 期刊名称:Source Code for Biology and Medicine
  • 印刷版ISSN:1751-0473
  • 电子版ISSN:1751-0473
  • 出版年度:2013
  • 卷号:8
  • 期号:1
  • 页码:10
  • DOI:10.1186/1751-0473-8-10
  • 语种:English
  • 出版社:BioMed Central
  • 摘要:Non-negative matrix factorization (NMF) has been introduced as an important method for mining biological data. Though there currently exists packages implemented in R and other programming languages, they either provide only a few optimization algorithms or focus on a specific application field. There does not exist a complete NMF package for the bioinformatics community, and in order to perform various data mining tasks on biological data. We provide a convenient MATLAB toolbox containing both the implementations of various NMF techniques and a variety of NMF-based data mining approaches for analyzing biological data. Data mining approaches implemented within the toolbox include data clustering and bi-clustering, feature extraction and selection, sample classification, missing values imputation, data visualization, and statistical comparison. A series of analysis such as molecular pattern discovery, biological process identification, dimension reduction, disease prediction, visualization, and statistical comparison can be performed using this toolbox.
  • 关键词:Non-negative matrix factorization ; Clustering ; Bi-clustering ; Feature extraction ; Feature selection ; Classification ; Missing values
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