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dc.contributor.author
Garcia-Albornoz, Manuel
dc.contributor.author
Nielsen, Jens
dc.date.accessioned
2019-04-24T12:43:15Z
dc.date.available
2017-06-12T00:02:35Z
dc.date.available
2019-04-17T16:35:21Z
dc.date.available
2019-04-24T12:43:15Z
dc.date.issued
2015
dc.identifier.issn
1752-0509
dc.identifier.other
10.1186/s12918-015-0184-9
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/112316
dc.identifier.doi
10.3929/ethz-b-000112316
dc.description.abstract
Background Understanding the underlying molecular mechanisms in human diseases is important for diagnosis and treatment of complex conditions and has traditionally been done by establishing associations between disorder-genes and their associated diseases. This kind of network analysis usually includes only the interaction of molecular components and shared genes. The present study offers a network and association analysis under a bioinformatics frame involving the integration of HUGO Gene Nomenclature Committee approved gene symbols, KEGG metabolic pathways and ICD-10-CM codes for the analysis of human diseases based on the level of inclusion and hypergeometric enrichment between genes and metabolic pathways shared by the different human disorders. Methods The present study offers the integration of HGNC approved gene symbols, KEGG metabolic pathways andICD-10-CM codes for the analysis of associations based on the level of inclusion and hypergeometricenrichment between genes and metabolic pathways shared by different diseases. Results 880 unique ICD-10-CM codes were mapped to the 4315 OMIM phenotypes and 3083 genes with phenotype-causing mutation. From this, a total of 705 ICD-10-CM codes were linked to 1587 genes with phenotype-causing mutations and 801 KEGG pathways creating a tripartite network composed by 15,455 code-gene-pathway interactions. These associations were further used for an inclusion analysis between diseases along with gene-disease predictions based on a hypergeometric enrichment methodology. Conclusions The results demonstrate that even though a large number of genes and metabolic pathways are shared between diseases of the same categories, inclusion levels between these genes and pathways are directional and independent of the disease classification. However, the gene-disease-pathway associations can be used for prediction of new gene-disease interactions that will be useful in drug discovery and therapeutic applications.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
KEGG Pathway
en_US
dc.subject
Mitogen Activate Protein Kinase Pathway
en_US
dc.subject
KEGG Database
en_US
dc.subject
Disease Network
en_US
dc.subject
HUGO Gene Nomenclature Committee
en_US
dc.title
Finding directionality and gene-disease predictions in disease associations
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2015-07-15
ethz.journal.title
BMC Systems Biology
ethz.journal.volume
9
en_US
ethz.journal.abbreviated
BMC syst. biol.
ethz.pages.start
35
en_US
ethz.size
8 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.nebis
005468370
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02020 - Dep. Chemie und Angewandte Biowiss. / Dep. of Chemistry and Applied Biosc.::02516 - Inst. f. Chemie- und Bioingenieurwiss. / Inst. Chemical and Bioengineering::03898 - Gunawan, Rudiyanto (ehemalig)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02020 - Dep. Chemie und Angewandte Biowiss. / Dep. of Chemistry and Applied Biosc.::02516 - Inst. f. Chemie- und Bioingenieurwiss. / Inst. Chemical and Bioengineering::03898 - Gunawan, Rudiyanto (ehemalig)
ethz.date.deposited
2017-06-12T00:05:08Z
ethz.source
ECIT
ethz.identifier.importid
imp593654127258759604
ethz.ecitpid
pub:173837
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-12T18:16:20Z
ethz.rosetta.lastUpdated
2019-04-24T12:43:30Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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