TMBETA-NET: discrimination and prediction of membrane spanning β-strands in outer membrane proteins. We have developed a web-server, TMBETA-NET for discriminating outer membrane proteins and predicting their membrane spanning β-strand segments. The amino acid compositions of globular and outer membrane proteins have been systematically analyzed and a statistical method has been proposed for discriminating outer membrane proteins. The prediction of membrane spanning segments is mainly based on feed forward neural network and refined with β-strand length. Our program takes the amino acid sequence as input and displays the type of the protein along with membrane-spanning β-strand segments as a stretch of highlighted amino acid residues. Further, the probability of residues to be in transmembrane β-strand has been provided with a coloring scheme. We observed that outer membrane proteins were discriminated with an accuracy of 89% and their membrane spanning β-strand segments at an accuracy of 73% just from amino acid sequence information. The prediction server is available at

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References in zbMATH (referenced in 2 articles )

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  1. Tran, Van Du T.; Chassignet, Philippe; Steyaert, Jean-Marc: On permuted super-secondary structures of transmembrane (\beta)-barrel proteins (2014)
  2. Gromiha, M. Michael; Ahmad, Shandar; Suwa, Makiko: TMBETA-NET: Discrimination and prediction of membrane spanning ß-strands in outer membrane proteins. (2005) ioport