Multi-order graph attention network for water solubility prediction and interpretation.

Lee, Sangho; Park, Hyunwoo; Choi, Chihyeon; Kim, Wonjoon; Kim, Ki Kang; Han, Young-Kyu; Kang, Joohoon; Kang, Chang-Jong; Son, Youngdoo

Lee, Sangho; Park, Hyunwoo; Choi, Chihyeon; Kim, Wonjoon; Kim, Ki Kang; Han, Young-Kyu; Kang, Joohoon; Kang, Chang-Jong; Son, Youngdoo.

Afiliação

Lee S; Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea.
Park H; Data Science Laboratory (DSLAB), Dongguk University-Seoul, Seoul, 04620, South Korea.
Choi C; Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea.
Kim W; Data Science Laboratory (DSLAB), Dongguk University-Seoul, Seoul, 04620, South Korea.
Kim KK; Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea.
Han YK; Data Science Laboratory (DSLAB), Dongguk University-Seoul, Seoul, 04620, South Korea.
Kang J; Division of Future Convergence (HCI Science Major), Dongduk Women's University, Seoul, 02748, South Korea.
Kang CJ; Department of Energy Science, Sungkyunkwan University (SKKU), Suwon, 16419, South Korea.
Son Y; Center for Integrated Nanostructure Physics (CINAP), Institute for Basic Science (IBS), Sungkyunkwan University (SKKU), Suwon, 16419, South Korea.

Sci Rep ; 13(1): 957, 2023 Mar 02.

Article em En | MEDLINE | ID: mdl-36864064

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Coréia do Sul País de publicação: Reino Unido

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