Hidden neural networks for transmembrane protein topology prediction

Hidden neural networks for transmembrane protein topology prediction

Hidden Markov Models (HMMs) are amongst the most successful methods for predicting protein features in biological sequence analysis. However, there are biological problems where the Markovian assumption is not sufficient since the sequence context can provide useful information for prediction purpos...

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Bibliographic Details
Main Authors: Ioannis A. Tamposis, Dimitra Sarantopoulou, Margarita C. Theodoropoulou, Evangelia A. Stasi, Panagiota I. Kontou, Konstantinos D. Tsirigos, Pantelis G. Bagos
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
Hidden Markov Models
Hidden Neural Networks
Membrane proteins
Sequence analysis
Neural Networks
Protein structure prediction
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037021004712

Internet

http://www.sciencedirect.com/science/article/pii/S2001037021004712

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