論文

査読有り
2016年4月

MetaMHCpan, A Meta Approach for Pan-Specific MHC Peptide Binding Prediction

Methods in Molecular Biology
  • Xu Yichang
  • ,
  • Luo Cheng
  • ,
  • Mamitsuka Hiroshi
  • ,
  • Zhu Shanfeng

1404
開始ページ
753
終了ページ
760
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/978-1-4939-3389-1_49
出版者・発行元
Springer Nature

Recent computational approaches in bioinformatics can achieve high performance, by which they can be a powerful support for performing real biological experiments, making biologists pay more attention to bioinformatics than before. In immunology, predicting peptides which can bind to MHC alleles is an important task, being tackled by many computational approaches. However, this situation causes a serious problem for immunologists to select the appropriate method to be used in bioinformatics. To overcome this problem, we develop an ensemble prediction-based Web server, which we call MetaMHCpan, consisting of two parts: MetaMHCIpan and MetaMHCIIpan, for predicting peptides which can bind MHC-I and MHC-II, respectively. MetaMHCIpan and MetaMHCIIpan use two (MHC2SKpan and LApan) and four (TEPITOPEpan, MHC2SKpan, LApan, and MHC2MIL) existing predictors, respectively. MetaMHCpan is available at http://​datamining-iip.​fudan.​edu.​cn/​MetaMHCpan/​index.​php/​pages/​view/​info.

リンク情報
DOI
https://doi.org/10.1007/978-1-4939-3389-1_49
CiNii Articles
http://ci.nii.ac.jp/naid/120005980847
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/27076335
URL
http://hdl.handle.net/2433/218453
ID情報
  • DOI : 10.1007/978-1-4939-3389-1_49
  • ISSN : 1064-3745
  • CiNii Articles ID : 120005980847
  • PubMed ID : 27076335

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