A meta decision tree approach for B-cell epitope mining

Yuh-Jyh Hu, Shun Ning You

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The ability of antibodies to respond to an antigen depends on the antibodies' specific recognition of epitopes, which are sites of the antigen to which antibodies bind. An increase in the availability of protein sequences and structures has enabled the identification of conformational epitopes, using various computational methods. The meta learner, among various approaches, has proved its feasibility and comparable accuracy in B-cell epitope prediction in previous studies. Nevertheless, its performance highly depends on the classification results of its multiple epitope base predictors within the meta learning architecture. We here propose bagging meta decision trees for epitope prediction to avoid the dependence on epitope prediction tools, and introduce 3D sphere-based attributes to improve prediction accuracy. Our experimental results demonstrate the superior performance of the bagging meta decision tree approach in comparison with single epitope predictors.

Original languageEnglish
Title of host publicationCIBCB 2016 - Annual IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467394727
DOIs
StatePublished - 28 Nov 2016
Event13th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2016 - Chiang Mai, Thailand
Duration: 5 Oct 20167 Oct 2016

Publication series

NameCIBCB 2016 - Annual IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology

Conference

Conference13th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2016
CountryThailand
CityChiang Mai
Period5/10/167/10/16

Keywords

  • B-cell
  • ensemble learning
  • epitope
  • meta decision tree

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