Predicting adverse drug reactions of two-drug combinations using structural and transcriptomic drug representations to train an artificial neural network.

Shankar, Susmitha; Bhandari, Ishita; Okou, David T; Srinivasa, Gowri; Athri, Prashanth

Shankar, Susmitha; Bhandari, Ishita; Okou, David T; Srinivasa, Gowri; Athri, Prashanth.

Afiliación

Shankar S; Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India.
Bhandari I; PES Center for Pattern Recognition, Department of Computer Science and Engineering, PES University, Bengaluru, India.
Okou DT; Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.
Srinivasa G; PES Center for Pattern Recognition, Department of Computer Science and Engineering, PES University, Bengaluru, India.
Athri P; Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India.

Chem Biol Drug Des ; 97(3): 665-673, 2021 03.

Article en En | MEDLINE | ID: mdl-33006799

Asunto(s)

Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos; Redes Neurales de la Computación; Bases de Datos Factuales; Combinación de Medicamentos; Interacciones Farmacológicas; Humanos; Transcriptoma

Palabras clave

ADR; LINCS L1000; TWOSIDES dataset; adverse drug reaction; artificial intelligence; artificial neural network; drug-drug interaction; transcriptomic data

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Redes Neurales de la Computación / Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Chem Biol Drug Des Asunto de la revista: BIOQUIMICA / FARMACIA / FARMACOLOGIA Año: 2021 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido

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