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J Comput Chem. 2004 Apr 15;25(5):762-7.

Neural network-based prediction of transmembrane beta-strand segments in outer membrane proteins.

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Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Aomi Frontier Building 17F, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan.


Prediction of transmembrane beta-strands in outer membrane proteins (OMP) is one of the important problems in computational chemistry and biology. In this work, we propose a method based on neural networks for identifying the membrane-spanning beta-strands. We introduce the concept of "residue probability" for assigning residues in transmembrane beta-strand segments. The performance of our method is evaluated with single-residue accuracy, correlation, specificity, and sensitivity. Our predicted segments show a good agreement with experimental observations with an accuracy level of 73% solely from amino acid sequence information. Further, the predictive power of N- and C-terminal residues in each segments, number of segments in each protein, and the influence of cutoff probability for identifying membrane-spanning beta-strands will be discussed. We have developed a Web server for predicting the transmembrane beta-strands from the amino acid sequence, and the prediction results are available at

[Indexed for MEDLINE]

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