Bioinformatics Vol. 18 no. 90002 2002
Pages S110-S115
© 2002 Oxford University Press
A similarity-based method for genome-wide prediction of disease-relevant human genes
1 Institute of Human Genetics, Bonn University Hospital, Wilhelmstr. 31, D-53111, Bonn, Germany
Received on April 8, 2002
; accepted on June 15, 2002
Motivation: A method for prediction of disease relevant human genes from the phenotypic appearance of a query disease is presented. Diseases of known genetic origin are clustered according to their phenotypic similarity. Each cluster entry consists of a disease and its underlying disease gene. Potential disease genes from the human genome are scored by their functional similarity to known disease genes in these clusters, which are phenotypically similar to the query disease.
Results:For assessment of the approach, a leave-one-out cross-validation of 878 diseases from the OMIM database, using 10672 candidate genes from the human genome, is performed. Depending on the applied parameters, in roughly one-third of cases the true solution is contained within the top scoring 3% of predictions and in two-third of cases the true solution is contained within the top scoring 15% of predictions.
The prediction results can either be used to identify target genes, when searching for a mutation in monogenic diseases or for selection of loci in genotyping experiments in genetically complex diseases.
Contact: jan.freudenberg{at}uni-bonn.de
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  S. Keerthikumar, S. Bhadra, K. Kandasamy, R. Raju, Y.L. Ramachandra, C. Bhattacharyya, K. Imai, O. Ohara, S. Mohan, and A. Pandey Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach DNA Res, December 1, 2009; 16(6): 345 - 351. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Schlicker and M. Albrecht FunSimMat update: new features for exploring functional similarity Nucleic Acids Res., November 18, 2009; (2009) gkp979v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. J. Jorgensen, I. Ruczinski, B. Kessing, M. W. Smith, Y. Y. Shugart, and A. J. Alberg Hypothesis-Driven Candidate Gene Association Studies: Practical Design and Analytical Considerations Am. J. Epidemiol., October 15, 2009; 170(8): 986 - 993. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Chen, E. E. Bardes, B. J. Aronow, and A. G. Jegga ToppGene Suite for gene list enrichment analysis and candidate gene prioritization Nucleic Acids Res., July 1, 2009; 37(suppl_2): W305 - W311. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. Nakazato, H. Bono, H. Matsuda, and T. Takagi Gendoo: Functional profiling of gene and disease features using MeSH vocabulary Nucleic Acids Res., July 1, 2009; 37(suppl_2): W166 - W169. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. J. Cai, E. Borenstein, R. Chen, and D. A. Petrov Similarly Strong Purifying Selection Acts on Human Disease Genes of All Evolutionary Ages Gen Biol Evol, June 22, 2009; 2009(0): 131 - 144. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. C. Tsoi, M. Boehnke, R. L. Klein, and W. J. Zheng Evaluation of genome-wide association study results through development of ontology fingerprints Bioinformatics, May 15, 2009; 25(10): 1314 - 1320. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Yilmaz, P. Jonveaux, C. Bicep, L. Pierron, M. Smail-Tabbone, and M.D. Devignes Gene-disease relationship discovery based on model-driven data integration and database view definition Bioinformatics, January 15, 2009; 25(2): 230 - 236. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Ozgur, T. Vu, G. Erkan, and D. R. Radev Identifying gene-disease associations using centrality on a literature mined gene-interaction network Bioinformatics, July 1, 2008; 24(13): i277 - i285. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Schlicker and M. Albrecht FunSimMat: a comprehensive functional similarity database Nucleic Acids Res., January 11, 2008; 36(suppl_1): D434 - D439. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Perez-Iratxeta, P. Bork, and M. A. Andrade-Navarro Update of the G2D tool for prioritization of gene candidates to inherited diseases Nucleic Acids Res., July 13, 2007; 35(suppl_2): W212 - W216. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. J. Gaulton, K. L. Mohlke, and T. J. Vision A computational system to select candidate genes for complex human traits Bioinformatics, May 1, 2007; 23(9): 1132 - 1140. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. A. George, J. Y. Liu, L. L. Feng, R. J. Bryson-Richardson, D. Fatkin, and M. A. Wouters Analysis of protein sequence and interaction data for candidate disease gene prediction Nucleic Acids Res., November 14, 2006; 34(19): e130 - e130. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Rossi, D. Masotti, C. Nardini, E. Bonora, G. Romeo, E. Macii, L. Benini, and S. Volinia TOM: a web-based integrated approach for identification of candidate disease genes. Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W285 - W292. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. A. Adie, R. R. Adams, K. L. Evans, D. J. Porteous, and B. S. Pickard SUSPECTS: enabling fast and effective prioritization of positional candidates Bioinformatics, March 15, 2006; 22(6): 773 - 774. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. Lopez-Bigas, B. J. Blencowe, and C. A. Ouzounis Highly consistent patterns for inherited human diseases at the molecular level Bioinformatics, February 1, 2006; 22(3): 269 - 277. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. Tiffin, J. F. Kelso, A. R. Powell, H. Pan, V. B. Bajic, and W. A. Hide Integration of text- and data-mining using ontologies successfully selects disease gene candidates Nucleic Acids Res., March 14, 2005; 33(5): 1544 - 1552. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. Lopez-Bigas and C. A. Ouzounis Genome-wide identification of genes likely to be involved in human genetic disease Nucleic Acids Res., June 4, 2004; 32(10): 3108 - 3114. [Abstract] [Full Text] [PDF]
|
|