Application of machine learning in understanding plant virus pathogenesis: trends and perspectives on emergence, diagnosis, host-virus interplay and management.

Ghosh, Dibyendu; Chakraborty, Srija; Kodamana, Hariprasad; Chakraborty, Supriya

Ghosh, Dibyendu; Chakraborty, Srija; Kodamana, Hariprasad; Chakraborty, Supriya.

Afiliação

Ghosh D; Molecular Virology Laboratory, School of Life Sciences, Jawaharlal Nehru University, New Delhi, 110067, India.
Chakraborty S; Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, 110016, India.
Kodamana H; Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, 110016, India.
Chakraborty S; School of Artificial Intelligence, Indian Institute of Technology Delhi, New Delhi, 110016, India.

Virol J ; 19(1): 42, 2022 03 09.

Article em En | MEDLINE | ID: mdl-35264189

Assuntos

Vírus de Plantas; Viroses; Algoritmos; Biologia Computacional/métodos; Vírus de DNA; Aprendizado de Máquina; Vírus de Plantas/genética; Plantas; Viroses/diagnóstico

Palavras-chave

Control options; Deep learning; Evolution and emergence; Host-virus interactions; Machine learning; Pathogenesis; Plant virus

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vírus de Plantas / Viroses Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Prognostic_studies / Qualitative_research Idioma: En Revista: Virol J Assunto da revista: VIROLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Índia País de publicação: Reino Unido

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