Secondary and Topological Structural Merge Prediction of Alpha-Helical Transmembrane Proteins Using a Hybrid Model Based on Hidden Markov and Long Short-Term Memory Neural Networks.

Gao, Ting; Zhao, Yutong; Zhang, Li; Wang, Han

Gao, Ting; Zhao, Yutong; Zhang, Li; Wang, Han.

Afiliação

Gao T; School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun 130117, China.
Zhao Y; School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun 130117, China.
Zhang L; School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China.
Wang H; School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun 130117, China.

Int J Mol Sci ; 24(6)2023 Mar 16.

Article em En | MEDLINE | ID: mdl-36982795

Assuntos

Algoritmos; Memória de Curto Prazo; Redes Neurais de Computação; Proteínas de Membrana/química; Estrutura Secundária de Proteína

Palavras-chave

class hidden markov model (CHMM); deep learning neural networks (DNNs); long short-term memory (LSTM) networks; merge prediction; secondary structure; topology structure; transmembrane protein

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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