A Deep Learning-Based Approach for Identifying the Medicinal Uses of Plant-Derived Natural Compounds.

Yoo, Sunyong; Yang, Hyung Chae; Lee, Seongyeong; Shin, Jaewook; Min, Seyoung; Lee, Eunjoo; Song, Minkeun; Lee, Doheon

Yoo, Sunyong; Yang, Hyung Chae; Lee, Seongyeong; Shin, Jaewook; Min, Seyoung; Lee, Eunjoo; Song, Minkeun; Lee, Doheon.

Afiliación

Yoo S; School of Electronics and Computer Engineering, Chonnam National University, Gwangju, South Korea.
Yang HC; Department of Otorhinolaryngology-Head and Neck Surgery, Chonnam National University Medical School and Chonnam National University Hospital, Gwangju, South Korea.
Lee S; School of Electronics and Computer Engineering, Chonnam National University, Gwangju, South Korea.
Shin J; School of Electronics and Computer Engineering, Chonnam National University, Gwangju, South Korea.
Min S; School of Electronics and Computer Engineering, Chonnam National University, Gwangju, South Korea.
Lee E; Big Data Steering Department, National Health Insurance Service, Wonju, South Korea.
Song M; Department of Physical and Rehabilitation Medicine, Research Institute of Medical Science, Cardiovascular Research Institute, Chonnam National University Medical School and Hospital, Gwangju, South Korea.
Lee D; Bio-Synergy Research Center, Daejeon, South Korea.

Front Pharmacol ; 11: 584875, 2020.

Article en En | MEDLINE | ID: mdl-33519445

Palabras clave

chemical property; deep learning; medicinal use; molecular interaction; natural compound; natural product; network analysis; text mining

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Pharmacol Año: 2020 Tipo del documento: Article País de afiliación: Corea del Sur Pais de publicación: Suiza

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