KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experiments
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...
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| Format: | Article |
| Language: | English |
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Elsevier
2015-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037015000185 |
| _version_ | 1817970219569643520 |
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| author | Eleftherios Pilalis Theodoros Koutsandreas Ioannis Valavanis Emmanouil Athanasiadis George Spyrou Aristotelis Chatziioannou |
| author_facet | Eleftherios Pilalis Theodoros Koutsandreas Ioannis Valavanis Emmanouil Athanasiadis George Spyrou Aristotelis Chatziioannou |
| author_sort | Eleftherios Pilalis |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T20:31:11Z |
| format | Article |
| id | doaj.art-5f4c6e5d250640bcb860feca77fc5867 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-04-13T20:31:11Z |
| publishDate | 2015-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-5f4c6e5d250640bcb860feca77fc58672022-12-22T02:31:10ZengElsevierComputational and Structural Biotechnology Journal2001-03702015-01-0113C24825510.1016/j.csbj.2015.03.009KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experimentsEleftherios Pilalis0Theodoros Koutsandreas1Ioannis Valavanis2Emmanouil Athanasiadis3George Spyrou4Aristotelis Chatziioannou5Metabolic Engineering and Bioinformatics Programme, Institute of Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, GreeceMetabolic Engineering and Bioinformatics Programme, Institute of Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, GreeceMetabolic Engineering and Bioinformatics Programme, Institute of Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, GreeceBiomedical Research Foundation, Academy of Athens, Athens, GreeceBiomedical Research Foundation, Academy of Athens, Athens, GreeceMetabolic Engineering and Bioinformatics Programme, Institute of Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, GreeceGene 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.http://www.sciencedirect.com/science/article/pii/S2001037015000185KEGGEnrichment analysisMolecular pathwaysGene expressionMicroarraysNext generation sequencing |
| spellingShingle | Eleftherios Pilalis Theodoros Koutsandreas Ioannis Valavanis Emmanouil Athanasiadis George Spyrou Aristotelis Chatziioannou KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experiments Computational and Structural Biotechnology Journal KEGG Enrichment analysis Molecular pathways Gene expression Microarrays Next generation sequencing |
| title | KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experiments |
| title_full | KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experiments |
| title_fullStr | KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experiments |
| title_full_unstemmed | KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experiments |
| title_short | KENeV: A web-application for the automated reconstruction and visualization of the enriched metabolic and signaling super-pathways deriving from genomic experiments |
| title_sort | kenev a web application for the automated reconstruction and visualization of the enriched metabolic and signaling super pathways deriving from genomic experiments |
| topic | KEGG Enrichment analysis Molecular pathways Gene expression Microarrays Next generation sequencing |
| url | http://www.sciencedirect.com/science/article/pii/S2001037015000185 |
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