MHC2AffyPred: A machine-learning approach to estimate affinity of MHC class II peptides based on structural interaction fingerprints.

Jani, Siddhi P; Kumar, Sivakumar Prasanth; Mangukia, Naman; Patel, Saumya K; Pandya, Himanshu A; Rawal, Rakesh M

Jani, Siddhi P; Kumar, Sivakumar Prasanth; Mangukia, Naman; Patel, Saumya K; Pandya, Himanshu A; Rawal, Rakesh M.

Afiliação

Jani SP; Department of Botany, Bioinformatics and Climate Change Impacts Management, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Kumar SP; Department of Botany, Bioinformatics and Climate Change Impacts Management, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Mangukia N; Department of Life Science, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Patel SK; Department of Botany, Bioinformatics and Climate Change Impacts Management, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Pandya HA; BioInnovations, Mumbai, Maharashtra, India.
Rawal RM; Department of Botany, Bioinformatics and Climate Change Impacts Management, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.

Proteins ; 91(2): 277-289, 2023 02.

Article em En | MEDLINE | ID: mdl-36116110

Assuntos

COVID-19; Humanos; Cadeias HLA-DRB1/metabolismo; Peptídeos/química; Antígenos HLA-DP/química; Antígenos HLA-DP/metabolismo; Antígenos HLA-DQ/química; Antígenos HLA-DQ/metabolismo; Aprendizado de Máquina; Ligação Proteica

Palavras-chave

MHC class II; MHC-II-peptide; SARS-CoV-2; immunoinformatics; machine-learning; random forest; structural interaction fingerprints

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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