KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species.

Hassani-Pak, Keywan; Singh, Ajit; Brandizi, Marco; Hearnshaw, Joseph; Parsons, Jeremy D; Amberkar, Sandeep; Phillips, Andrew L; Doonan, John H; Rawlings, Chris

Hassani-Pak, Keywan; Singh, Ajit; Brandizi, Marco; Hearnshaw, Joseph; Parsons, Jeremy D; Amberkar, Sandeep; Phillips, Andrew L; Doonan, John H; Rawlings, Chris.

Afiliação

Hassani-Pak K; Rothamsted Research, Harpenden, UK.
Singh A; Rothamsted Research, Harpenden, UK.
Brandizi M; Rothamsted Research, Harpenden, UK.
Hearnshaw J; Rothamsted Research, Harpenden, UK.
Parsons JD; Rothamsted Research, Harpenden, UK.
Amberkar S; Rothamsted Research, Harpenden, UK.
Phillips AL; Rothamsted Research, Harpenden, UK.
Doonan JH; IBERS, Aberystwyth University, Aberystwyth, UK.
Rawlings C; Rothamsted Research, Harpenden, UK.

Plant Biotechnol J ; 19(8): 1670-1678, 2021 08.

Article em En | MEDLINE | ID: mdl-33750020

Assuntos

COVID-19; Herança Multifatorial; Estudos de Associação Genética; Humanos; Melhoramento Vegetal; SARS-CoV-2

Palavras-chave

bioinformatics; candidate gene prioritization; data integration; exploratory data mining; gene discovery; gene network; information visualization; knowledge discovery; knowledge graph; systems biology

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Herança Multifatorial / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Plant Biotechnol J Assunto da revista: BIOTECNOLOGIA / BOTANICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido

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