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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Autores principales: Ioannis A. Tamposis, Dimitra Sarantopoulou, Margarita C. Theodoropoulou, Evangelia A. Stasi, Panagiota I. Kontou, Konstantinos D. Tsirigos, Pantelis G. Bagos
Formato: article
Lenguaje:EN
Publicado: Elsevier 2021
Materias:
Hidden Markov Models
Hidden Neural Networks
Membrane proteins
Sequence analysis
Neural Networks
Protein structure prediction
Biotechnology
TP248.13-248.65
Acceso en línea:https://doaj.org/article/1826dcfedd9741849193e7818f992144
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https://doaj.org/article/1826dcfedd9741849193e7818f992144

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