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    BMCBI
    2007
    173views more  BMCBI 2007»
    Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
    13 years 7 months ago
    Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
    Download  www.biomedcentral.com
    Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
    Malik Yousef, Segun Jung, Louise C. Showe, Michael...
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    KDD
    2004
    ACM
    139views Data Mining» more  KDD 2004»
    Learning a complex metabolomic dataset using random forests and support vector machines
    14 years 8 months ago
    Learning a complex metabolomic dataset using random forests and support vector machines
    Download  math.uc.edu
    Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
    Young Truong, Xiaodong Lin, Chris Beecher
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    ICMLA
    2010
    133views Machine Learning» more  ICMLA 2010»
    Smoothing Gene Expression Using Biological Networks
    13 years 5 months ago
    Smoothing Gene Expression Using Biological Networks
    Download  math.bu.edu
    Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
    Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
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    BMCBI
    2005
    155views more  BMCBI 2005»
    Mining protein function from text using term-based support vector machines
    13 years 7 months ago
    Mining protein function from text using term-based support vector machines
    Download  www.biomedcentral.com
    Background: Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We...
    Simon B. Rice, Goran Nenadic, Benjamin J. Stapley
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    EVOW
    2006
    Springer
    136views Artificial Intelligence» more  EVOW 2006»
    Human Papillomavirus Risk Type Classification from Protein Sequences Using Support Vector Machines
    13 years 11 months ago
    Human Papillomavirus Risk Type Classification from Protein Sequences Using Support Vector Machines
    Download  bi.snu.ac.kr
    Infection by the human papillomavirus (HPV) is associated with the development of cervical cancer. HPV can be classified to highand low-risk type according to its malignant potenti...
    Sun Kim, Byoung-Tak Zhang
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