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Characterization and comparison of gene-centered human interactomes.
Mosca, Ettore; Bersanelli, Matteo; Matteuzzi, Tommaso; Di Nanni, Noemi; Castellani, Gastone; Milanesi, Luciano; Remondini, Daniel.
Afiliación
  • Mosca E; Institute of Biomedical Technologies, National Research Council, Segrate (Milan), 20090, Italy.
  • Bersanelli M; Humanitas University, Department of Biomedical Sciences, Pieve Emanuele (Milan), 20090, Italy.
  • Matteuzzi T; Department of Physics and Astronomy, University of Bologna, Bologna, 40127, Italy.
  • Di Nanni N; Institute of Biomedical Technologies, National Research Council, Segrate (Milan), 20090, Italy.
  • Castellani G; Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, 40127, Italy.
  • Milanesi L; Institute of Biomedical Technologies, National Research Council, Segrate (Milan), 20090, Italy.
  • Remondini D; Department of Physics and Astronomy, University of Bologna, Bologna, 40127, Italy.
Brief Bioinform ; 22(6)2021 11 05.
Article en En | MEDLINE | ID: mdl-34010955
ABSTRACT
The complex web of macromolecular interactions occurring within cells-the interactome-is the backbone of an increasing number of studies, but a clear consensus on the exact structure of this network is still lacking. Different genome-scale maps of human interactome have been obtained through several experimental techniques and functional analyses. Moreover, these maps can be enriched through literature-mining approaches, and different combinations of various 'source' databases have been used in the literature. It is therefore unclear to which extent the various interactomes yield similar results when used in the context of interactome-based approaches in network biology. We compared a comprehensive list of human interactomes on the basis of topology, protein complexes, molecular pathways, pathway cross-talk and disease gene prediction. In a general context of relevant heterogeneity, our study provides a series of qualitative and quantitative parameters that describe the state of the art of human interactomes and guidelines for selecting interactomes in future applications.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Biología Computacional / Perfilación de la Expresión Génica / Redes Reguladoras de Genes / Transcriptoma Tipo de estudio: Prognostic_studies / Qualitative_research Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Biología Computacional / Perfilación de la Expresión Génica / Redes Reguladoras de Genes / Transcriptoma Tipo de estudio: Prognostic_studies / Qualitative_research Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Italia