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Bioinformatics methodologies for coeliac disease and its comorbidities.
Del Prete, Eugenio; Facchiano, Angelo; Liò, Pietro.
Afiliação
  • Del Prete E; Department of Sciences, University of Basilicata, Via dell'Ateneo Lucano, Potenza, Italy.
  • Facchiano A; National Research Council, Institute of Food Science (CNR-ISA),Via Roma 64, Avellino, Italy.
  • Liò P; Computer Laboratory, University of Cambridge, JJ Thomson Ave., Cambridge, UK.
Brief Bioinform ; 21(1): 355-367, 2020 Jan 17.
Article em En | MEDLINE | ID: mdl-30452543
ABSTRACT
Coeliac disease (CD) is a complex, multifactorial pathology caused by different factors, such as nutrition, immunological response and genetic factors. Many autoimmune diseases are comorbidities for CD, and a comprehensive and integrated analysis with bioinformatics approaches can help in evaluating the interconnections among all the selected pathologies. We first performed a detailed survey of gene expression data available in public repositories on CD and less commonly considered comorbidities. Then we developed an innovative pipeline that integrates gene expression, cell-type data and online resources (e.g. a list of comorbidities from the literature), using bioinformatics methods such as gene set enrichment analysis and semantic similarity. Our pipeline is written in R language, available at the following link http//bioinformatica.isa.cnr.it/COELIAC_DISEASE/SCRIPTS/. We found a list of common differential expressed genes, gene ontology terms and pathways among CD and comorbidities and the closeness among the selected pathologies by means of disease ontology terms. Physicians and other researchers, such as molecular biologists, systems biologists and pharmacologists can use it to analyze pathology in detail, from differential expressed genes to ontologies, performing a comparison with the pathology comorbidities or with other diseases.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article