Prediction of t-cell epitopes using support vector machine and similarity kernel

  • Authors:

  • Feng Shi;Jing Huang

  • Affiliations:

  • School of Science, Huazhong Agricultural University, Wuhan, China;School of Computer Science, Wuhan University, Wuhan, China

  • Venue:
  • CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
  • Year:
  • 2005

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Abstract

T-cell activation is a pivotal process in immune response. A precondition for this activation is the recognition of antigenic epitopes by T-cell receptors. This recognition is antigen-specific. Therefore, identifying the pattern of a MHC restricted T-cell epitopes is of great importance for immunotherapies and vaccine design. In this paper, a new kernel is proposed to use together with support vector machine for the direct prediction of T-cell epitope. The experiment was carried on an MHC type I restricted T-cell clone LAU203-1.5. The results suggest that this approach is efficient and promising.