TSFSOM: Transmembrane Segments Prediction by Fuzzy Self-Organizing Map

  • Yong Deng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)


A novel method based on fuzzy Self-Organizing Map to detect the transmembrane segments, called TSFSOM, is presented in the paper. The multivariate ”time” series of transmembrane proteins are classified by fuzzy Self-Organizing Map into five classes. Through the analysis of resulting trajectories on the map, frequent patterns of transmembrane segments are detected and even some kind of ”new” knowledge about membrane insertion mechanism is obtained. The discovered patterns and the knowledge are then used to predict transmembrane segments for query sequence. The prediction results not only show that the method is powerful, but also prove that the patterns and the knowledge about the interaction between the patterns are effective and acceptable.


Frequent Pattern Transmembrane Helix Transmembrane Segment Membrane Segment Membrane Protein Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yong Deng
    • 1
  1. 1.Zhejiang Police Vocational AcademyHangzhouChina

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