FFMAVP: a new classifier based on feature fusion and multitask learning for identifying antiviral peptides and their subclasses.

Cao, Ruifen; Hu, Weiling; Wei, Pijing; Ding, Yun; Bin, Yannan; Zheng, Chunhou

Cao, Ruifen; Hu, Weiling; Wei, Pijing; Ding, Yun; Bin, Yannan; Zheng, Chunhou.

Afiliação

Cao R; Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Computer Science and Technology, Anhui University.
Hu W; Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Computer Science and Technology, Anhui University.
Wei P; Institutes of Physical Science and Information Technology, Anhui University.
Ding Y; Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Artificial Intelligence, Anhui University.
Bin Y; Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University.
Zheng C; Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Artificial Intelligence, Anhui University.

Brief Bioinform ; 24(6)2023 09 22.

Article em En | MEDLINE | ID: mdl-37861174

Assuntos

Algoritmos; Peptídeos; Peptídeos/química; Redes Neurais de Computação; Aprendizado de Máquina; Antivirais/farmacologia; Antivirais/química

Palavras-chave

antiviral peptides; fusion feature; multiclass task; multitask learning; two-stage prediction tool

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Algoritmos Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo

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XML

PubMed Links

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Algoritmos Idioma: En Ano de publicação: 2023 Tipo de documento: Article