Please use this identifier to cite or link to this item: https://doi.org/10.1109/TCBB.2011.49
DC FieldValue
dc.titleAntibody-specified B-cell epitope prediction in line with the principle of context-awareness
dc.contributor.authorZhao, L.
dc.contributor.authorWong, L.
dc.contributor.authorLi, J.
dc.date.accessioned2013-07-04T07:46:59Z
dc.date.available2013-07-04T07:46:59Z
dc.date.issued2011
dc.identifier.citationZhao, L., Wong, L., Li, J. (2011). Antibody-specified B-cell epitope prediction in line with the principle of context-awareness. IEEE/ACM Transactions on Computational Biology and Bioinformatics 8 (6) : 1483-1494. ScholarBank@NUS Repository. https://doi.org/10.1109/TCBB.2011.49
dc.identifier.issn15455963
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39674
dc.description.abstractContext-awareness is a characteristic in the recognition between antigens and antibodies, highlighting the reconfiguration of epitope residues when an antigen interacts with a different antibody. A coarse binary classification of antigen regions into epitopes, or nonepitopes without specifying antibodies may not accurately reflect this biological reality. Therefore, we study an antibody-specified epitope prediction problem in line with this principle. This problem is new and challenging as we pinpoint a subset of the antigenic residues from an antigen when it binds to a specific antibody. We introduce two kinds of associations of the contextual awareness: 1) residues-residues pairing preference, and 2) the dependence between sets of contact residue pairs. Preference plays a bridging role to link interacting paratope and epitope residues while dependence is used to extend the association from one-dimension to two-dimension. The paratope/epitope residues' relative composition, cooperativity ratios, and Markov properties are also utilized to enhance our method. A nonredundant data set containing 80 antibody-antigen complexes is compiled and used in the evaluation. The results show that our method yields a good performance on antibody-specified epitope prediction. On the traditional antibody-ignored epitope prediction problem, a simplified version of our method can produce a competitive, sometimes much better, performance in comparison with three structure-based predictors. © 2011 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TCBB.2011.49
dc.sourceScopus
dc.subjectantibody
dc.subjectantigen.
dc.subjectcontext dependence
dc.subjectEpitope prediction
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/TCBB.2011.49
dc.description.sourcetitleIEEE/ACM Transactions on Computational Biology and Bioinformatics
dc.description.volume8
dc.description.issue6
dc.description.page1483-1494
dc.identifier.isiut000294782100004
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