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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Detalles Bibliográficos
Autores principales: Tamposis, Ioannis A., Sarantopoulou, Dimitra, Theodoropoulou, Margarita C., Stasi, Evangelia A., Kontou, Panagiota I., Tsirigos, Konstantinos D., Bagos, Pantelis G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606341/
https://www.ncbi.nlm.nih.gov/pubmed/34849210
http://dx.doi.org/10.1016/j.csbj.2021.11.006

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606341/
https://www.ncbi.nlm.nih.gov/pubmed/34849210
http://dx.doi.org/10.1016/j.csbj.2021.11.006

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