Identification of candidate disease genes by integrating Gene Ontologies and protein-interaction networks: case study of primary immunodeficiencies.
Ortutay, Csaba and Vihinen, Mauno LU
(2009)
In Nucleic Acids Research
37(2).
p.622-628
- Abstract
- Disease gene identification is still a challenge despite modern high-throughput methods. Many diseases are very rare or lethal and thus cannot be investigated with traditional methods. Several in silico methods have been developed but they have some limitations. We introduce a new method that combines information about protein-interaction network properties and Gene Ontology terms. Genes with high-calculated network scores and statistically significant gene ontology terms based on known diseases are prioritized as candidate genes. The method was applied to identify novel primary immunodeficiency-related genes, 26 of which were found. The investigation uses the protein-interaction network for all essential immunome human genes available in... (More)
- Disease gene identification is still a challenge despite modern high-throughput methods. Many diseases are very rare or lethal and thus cannot be investigated with traditional methods. Several in silico methods have been developed but they have some limitations. We introduce a new method that combines information about protein-interaction network properties and Gene Ontology terms. Genes with high-calculated network scores and statistically significant gene ontology terms based on known diseases are prioritized as candidate genes. The method was applied to identify novel primary immunodeficiency-related genes, 26 of which were found. The investigation uses the protein-interaction network for all essential immunome human genes available in the Immunome Knowledge Base and an analysis of their enriched gene ontology annotations. The identified disease gene candidates are mainly involved in cellular signaling including receptors, protein kinases and adaptor and binding proteins as well as enzymes. The method can be generalized for any disease group with sufficient information. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3634998
- author
- Ortutay, Csaba
and Vihinen, Mauno
LU
- publishing date
- 2009
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Computational Biology: methods, Immunologic Deficiency Syndromes: genetics, Proteins: genetics
- in
- Nucleic Acids Research
- volume
- 37
- issue
- 2
- pages
- 622 - 628
- publisher
- Oxford University Press
- external identifiers
-
- pmid:19073697
- scopus:59649111554
- ISSN
- 1362-4962
- DOI
- 10.1093/nar/gkn982
- language
- English
- LU publication?
- no
- id
- 2b703ed7-a954-432e-b229-ebbfad1c9c07 (old id 3634998)
- alternative location
- http://www.ncbi.nlm.nih.gov/pubmed/19073697?dopt=Abstract
- date added to LUP
- 2016-04-04 07:08:05
- date last changed
- 2022-01-29 01:44:16
@article{2b703ed7-a954-432e-b229-ebbfad1c9c07,
abstract = {{Disease gene identification is still a challenge despite modern high-throughput methods. Many diseases are very rare or lethal and thus cannot be investigated with traditional methods. Several in silico methods have been developed but they have some limitations. We introduce a new method that combines information about protein-interaction network properties and Gene Ontology terms. Genes with high-calculated network scores and statistically significant gene ontology terms based on known diseases are prioritized as candidate genes. The method was applied to identify novel primary immunodeficiency-related genes, 26 of which were found. The investigation uses the protein-interaction network for all essential immunome human genes available in the Immunome Knowledge Base and an analysis of their enriched gene ontology annotations. The identified disease gene candidates are mainly involved in cellular signaling including receptors, protein kinases and adaptor and binding proteins as well as enzymes. The method can be generalized for any disease group with sufficient information.}},
author = {{Ortutay, Csaba and Vihinen, Mauno}},
issn = {{1362-4962}},
keywords = {{Computational Biology: methods; Immunologic Deficiency Syndromes: genetics; Proteins: genetics}},
language = {{eng}},
number = {{2}},
pages = {{622--628}},
publisher = {{Oxford University Press}},
series = {{Nucleic Acids Research}},
title = {{Identification of candidate disease genes by integrating Gene Ontologies and protein-interaction networks: case study of primary immunodeficiencies.}},
url = {{http://dx.doi.org/10.1093/nar/gkn982}},
doi = {{10.1093/nar/gkn982}},
volume = {{37}},
year = {{2009}},
}