Volume 28 Issue 6
Jun.  2015
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Article Navigation >  Biomedical and Environmental Sciences  > 2015  >  28(6): 460-463

LIAN Yao, HUANG Ze Chi, GE Meng, PAN Xian Ming. An Improved Method for Predicting Linear B-cell Epitope Using Deep Maxout Networks[J]. Biomedical and Environmental Sciences, 2015, 28(6): 460-463. doi: 10.3967/bes2015.065
Citation: LIAN Yao, HUANG Ze Chi, GE Meng, PAN Xian Ming. An Improved Method for Predicting Linear B-cell Epitope Using Deep Maxout Networks[J]. Biomedical and Environmental Sciences, 2015, 28(6): 460-463. doi: 10.3967/bes2015.065
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An Improved Method for Predicting Linear B-cell Epitope Using Deep Maxout Networks

doi: 10.3967/bes2015.065

  • The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing 100084, China

  • Key Laboratory of Protein and Peptide Pharmaceutical, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China

  • CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China

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    沈阳化工大学材料科学与工程学院 沈阳 110142

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An Improved Method for Predicting Linear B-cell Epitope Using Deep Maxout Networks

doi: 10.3967/bes2015.065
  • The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing 100084, China
  • Key Laboratory of Protein and Peptide Pharmaceutical, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
  • CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
LIAN Yao, HUANG Ze Chi, GE Meng, PAN Xian Ming. An Improved Method for Predicting Linear B-cell Epitope Using Deep Maxout Networks[J]. Biomedical and Environmental Sciences, 2015, 28(6): 460-463. doi: 10.3967/bes2015.065
Citation: LIAN Yao, HUANG Ze Chi, GE Meng, PAN Xian Ming. An Improved Method for Predicting Linear B-cell Epitope Using Deep Maxout Networks[J]. Biomedical and Environmental Sciences, 2015, 28(6): 460-463. doi: 10.3967/bes2015.065
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    Funds:  This study was supported by grant 2009CB918801 from the Ministry of Science and Technology of China

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