Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Prediction of Transmembrane Protein Topology Using Position-specific Modeling of Context-dependent Structural Regions

  • Chi, Sang-Mun (Department of Computer Science, College of Multimedia, Kyungsung University)
  • Published : 2005.08.31
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Abstract

This paper presents a new transmembrane Protein topology prediction method which is an attempt to model the topological rules governing the topogenesis of transmembrane proteins. Context-dependent structural regions of the transmembrane protein are used as basic modeling units in order to effectively represent their topogenic roles during transmembrane protein assembly. These modeling units are modeled by means of a tied-state hidden Markov model, which can express the position-specific effect of amino acids during ransmembrane protein assembly. The performance of prediction improves with these modeling approaches. In particular, marked improvement of orientation prediction shows the validity of the proposed modeling. The proposed method is available at http://bioroutine.com/TRAPTOP.

Keywords

References

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