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GenCoNet - A Graph Database for the Analysis of Comorbidities by Gene Networks.
Shoshi, Alban; Hofestädt, Ralf; Zolotareva, Olga; Friedrichs, Marcel; Maier, Alex; Ivanisenko, Vladimir A; Dosenko, Victor E; Bragina, Elena Yu.
Afiliação
  • Shoshi A; Bielefeld University, Bioinformatics/Medical Informatics Department, Bielefeld, Germany.
  • Hofestädt R; Bielefeld University, Bioinformatics/Medical Informatics Department, Bielefeld, Germany.
  • Zolotareva O; Bielefeld University, Bioinformatics/Medical Informatics Department, Bielefeld, Germany.
  • Friedrichs M; Bielefeld University, International Research Group "Computational Methods for the Analysis of the Diversity and Dynamics of Genomes", Bielefeld, Germany.
  • Maier A; Bielefeld University, Bioinformatics/Medical Informatics Department, Bielefeld, Germany.
  • Ivanisenko VA; Bielefeld University, Bioinformatics/Medical Informatics Department, Bielefeld, Germany.
  • Dosenko VE; Institute of Cytology and Genetics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia.
  • Bragina EY; Bogomoletz Institute of Physiology, Kiev, Ukraine.
J Integr Bioinform ; 15(4)2018 Dec 25.
Article em En | MEDLINE | ID: mdl-30864352
ABSTRACT
The prevalence of comorbid diseases poses a major health issue for millions of people worldwide and an enormous socio-economic burden for society. The molecular mechanisms for the development of comorbidities need to be investigated. For this purpose, a workflow system was developed to aggregate data on biomedical entities from heterogeneous data sources. The process of integrating and merging all data sources of the workflow system was implemented as a semi-automatic pipeline that provides the import, fusion, and analysis of the highly connected biomedical data in a Neo4j database GenCoNet. As a starting point, data on the common comorbid diseases essential hypertension and bronchial asthma was integrated. GenCoNet (https//genconet.kalis-amts.de) is a curated database that provides a better understanding of hereditary bases of comorbidities.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Asma / Gráficos por Computador / Software / Bases de Dados Factuais / Biologia Computacional / Redes Reguladoras de Genes / Hipertensão Essencial Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Asma / Gráficos por Computador / Software / Bases de Dados Factuais / Biologia Computacional / Redes Reguladoras de Genes / Hipertensão Essencial Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article