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KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experiments.
Pilalis, Eleftherios; Koutsandreas, Theodoros; Valavanis, Ioannis; Athanasiadis, Emmanouil; Spyrou, George; Chatziioannou, Aristotelis.
Afiliación
  • Pilalis E; Metabolic Engineering and Bioinformatics Programme, Institute of Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece.
  • Koutsandreas T; Metabolic Engineering and Bioinformatics Programme, Institute of Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece.
  • Valavanis I; Metabolic Engineering and Bioinformatics Programme, Institute of Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece.
  • Athanasiadis E; Biomedical Research Foundation, Academy of Athens, Athens, Greece.
  • Spyrou G; Biomedical Research Foundation, Academy of Athens, Athens, Greece.
  • Chatziioannou A; Metabolic Engineering and Bioinformatics Programme, Institute of Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece.
Comput Struct Biotechnol J ; 13: 248-55, 2015.
Article en En | MEDLINE | ID: mdl-26925206
ABSTRACT
Gene expression analysis, using high throughput genomic technologies,has become an indispensable step for the meaningful interpretation of the underlying molecular complexity, which shapes the phenotypic manifestation of the investigated biological mechanism. The modularity of the cellular response to different experimental conditions can be comprehended through the exploitation of molecular pathway databases, which offer a controlled, curated background for statistical enrichment analysis. Existing tools enable pathway analysis, visualization, or pathway merging but none integrates a fully automated workflow, combining all above-mentioned modules and destined to non-programmer users. We introduce an online web application, named KEGG Enriched Network Visualizer (KENeV), which enables a fully automated workflow starting from a list of differentially expressed genes and deriving the enriched KEGG metabolic and signaling pathways, merged into two respective, non-redundant super-networks. The final networks can be downloaded as SBML files, for further analysis, or instantly visualized through an interactive visualization module. In conclusion, KENeV (available online at http//www.grissom.gr/kenev) provides an integrative tool, suitable for users with no programming experience, for the functional interpretation, at both the metabolic and signaling level, of differentially expressed gene subsets deriving from genomic experiments.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Año: 2015 Tipo del documento: Article País de afiliación: Grecia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Año: 2015 Tipo del documento: Article País de afiliación: Grecia