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    » Predicting Nucleolar Proteins Using Support-Vector Machines
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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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    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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    BMCBI
    2010
    159views more  BMCBI 2010»
    Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
    13 years 7 months ago
    Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
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    Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
    Alvaro J. González, Li Liao
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    BMCBI
    2007
    127views more  BMCBI 2007»
    Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines
    13 years 7 months ago
    Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines
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    Background: Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occur approximately every 1000 bases in the overall human population. The no...
    Jian Tian, Ningfeng Wu, Xuexia Guo, Jun Guo, Juhua...
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    BMCBI
    2010
    151views more  BMCBI 2010»
    Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
    13 years 7 months ago
    Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
    Download  www.biomedcentral.com
    Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
    Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou
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