Assessment of vector-host-pathogen relationships using data mining and machine learning.

Agany, Diing D M; Pietri, Jose E; Gnimpieba, Etienne Z

Agany, Diing D M; Pietri, Jose E; Gnimpieba, Etienne Z.

Afiliación

Agany DDM; University of South Dakota, Biomedical Engineering Program, Sioux Falls, SD, United States.
Pietri JE; 2DBEST (2-Dimensional Materials for Biofilm Engineering, Science and Technology), United States.
Gnimpieba EZ; University of South Dakota, Sanford School of Medicine, Division of Basic Biomedical Sciences, Vermillion, SD, United States.

Comput Struct Biotechnol J ; 18: 1704-1721, 2020.

Article en En | MEDLINE | ID: mdl-32670510

Palabras clave

Adaptation; Association Mining; Big Data; Data Mining; Host-Pathogen; Infectious Disease; Interaction; Machine Learning; OMICs; Pathogenicity; Systems Bioscience; Transmission; Vector-Borne Disease

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Comput Struct Biotechnol J Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

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