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Activeperl 5.16.1 download7/1/2023 Received: SeptemAccepted: DecemPublished: December 22, 2015Ĭopyright: © 2015 Roy Choudhury, Novič. Permyakov, Russian Academy of Sciences, Institute for Biological Instrumentation, RUSSIAN FEDERATION Ĭitation: Roy Choudhury A, Novič M (2015) PredβTM: A Novel β-Transmembrane Region Prediction Algorithm. PredβTM can be freely accessed on the web at. Further, we applied PredβTM to analyze the β-barrel membrane proteins without defined transmembrane regions and the uncharacterized protein sequences in eight bacterial genomes and predict possible β-transmembrane proteins. In comparison with other state-of-art methods, PredβTM provides a higher precision and segment overlap without compromising with sensitivity. With a benchmark set of 35 β-transmembrane proteins, PredβTM shows a sensitivity and precision of 83.71% and 72.98%, respectively. The predictor does not incorporate evolutionary profile information explicitly, but is based on sequence patterns generated implicitly by encoding the protein segments using amino acid adjacency matrix. Position-specific amino acid preference data is incorporated in the final prediction. Using amino acid pair frequency information in known β-transmembrane protein sequences, we have trained a support vector machine classifier to predict β-transmembrane segments. Here, we describe PredβTM, a transmembrane region prediction algorithm for β-barrel proteins. Despite significant efforts, currently available β-transmembrane region predictors are still limited in terms of prediction accuracy, especially in precision. Predicting the transmembrane regions is an important aspect of understanding the structures and architecture of different β-barrel membrane proteins.
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