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Bioinformatic tools for exploring the SUMO gene network: An update

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Detalhes bibliográficos
Resumo:Plant sumoylation research has seen significant advances in recent years, particularly since high-throughput proteomic strategies have enabled the discovery of more than one thousand SUMO targets. In the present chapter, we update the previously reported SUMO (small ubiquitin-related modifier) gene network (SGN) to its v4 iteration. SGN is a curated assembly of Arabidopsis thaliana genes that have been functionally associated with sumoylation, from SUMO pathway components to targets and interactors. The enclosed tutorial helps interpret and manage these datasets and details bioinformatic tools that can be used for in silico-based hypothesis generation. The latter include tools for sumoylation site prediction, comparative genomics, and gene network analysis.
Autores principais:Castro, Pedro Humberto
Outros Autores:Santos, Miguel Ângelo; Magalhães, Alexandre Papadopoulos; Tavares, R. M.; Azevedo, Herlander
Assunto:Arabidopsis Bioinformatics Data mining Functional categorization Gene expression Gene network Posttranslational modification Small ubiquitin-related modifier (SUMO)
Ano:2023
País:Portugal
Tipo de documento:capítulo de livro
Tipo de acesso:acesso restrito
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:Plant sumoylation research has seen significant advances in recent years, particularly since high-throughput proteomic strategies have enabled the discovery of more than one thousand SUMO targets. In the present chapter, we update the previously reported SUMO (small ubiquitin-related modifier) gene network (SGN) to its v4 iteration. SGN is a curated assembly of Arabidopsis thaliana genes that have been functionally associated with sumoylation, from SUMO pathway components to targets and interactors. The enclosed tutorial helps interpret and manage these datasets and details bioinformatic tools that can be used for in silico-based hypothesis generation. The latter include tools for sumoylation site prediction, comparative genomics, and gene network analysis.