NGS data vectorization, clustering, and finding key codons in SARS-CoV-2 variations.

Kim, Juhyeon; Cheon, Saeyeon; Ahn, Insung

Kim, Juhyeon; Cheon, Saeyeon; Ahn, Insung.

Afiliação

Kim J; Department of Data-Centric Problem Solving Research, Korea Institute of Science and Technology Information, Yuseong-gu, Daejeon, Korea.
Cheon S; Center for Convergent Research of Emerging Virus Infection, Korea Research Institute of Chemical Technology, Yuseong-gu, Daejeon, Korea.
Ahn I; Department of Industrial Engineering, Ajou University, Suwon, South Korea.

BMC Bioinformatics ; 23(1): 187, 2022 May 17.

Article em En | MEDLINE | ID: mdl-35581558

Assuntos

COVID-19; Magnoliopsida; Análise por Conglomerados; Códon; Aprendizado de Máquina; SARS-CoV-2/genética

Palavras-chave

Clustering; Density based spatial clustering of applications with noise; Feature selection; Protein sequence analysis; Random forest; SARS-CoV-2; Sequence data pre-process; Shapely value; t-Stochastic neighbour embedding

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Magnoliopsida / COVID-19 Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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