G2D: a Tool for Mining Genes Associated with Disease

Overview

Journal BMC Genet

Publisher Biomed Central

Specialties Biotechnology
Molecular Biology

Date 2005 Aug 24

PMID 16115313

Citations 55

Authors

Carolina Perez-Iratxeta

Matthias Wjst

Peer Bork

Miguel A Andrade

Affiliations

Soon will be listed here.

Abstract

Background: Human inherited diseases can be associated by genetic linkage with one or more genomic regions. The availability of the complete sequence of the human genome allows examining those locations for an associated gene. We previously developed an algorithm to prioritize genes on a chromosomal region according to their possible relation to an inherited disease using a combination of data mining on biomedical databases and gene sequence analysis.

Results: We have implemented this method as a web application in our site G2D (Genes to Diseases). It allows users to inspect any region of the human genome to find candidate genes related to a genetic disease of their interest. In addition, the G2D server includes pre-computed analyses of candidate genes for 552 linked monogenic diseases without an associated gene, and the analysis of 18 asthma loci.

Conclusion: G2D can be publicly accessed at http://www.ogic.ca/projects/g2d_2/.

Citing Articles

Liu Y, Wu Q, Zhou L, Liu Y, Li C, Wei Z BMC Genomics. 2024; 25(1):1161.

PMID: 39623332 PMC: 11610307. DOI: 10.1186/s12864-024-11078-4.

NADPH Oxidase 3: Beyond the Inner Ear.

Herb M Antioxidants (Basel). 2024; 13(2).

PMID: 38397817 PMC: 10886416. DOI: 10.3390/antiox13020219.

Application of Bidirectional Generative Adversarial Networks to Predict Potential miRNAs Associated With Diseases.

Xu L, Li X, Yang Q, Tan L, Liu Q, Liu Y Front Genet. 2022; 13:936823.

PMID: 35903359 PMC: 9314862. DOI: 10.3389/fgene.2022.936823.

ANMDA: anti-noise based computational model for predicting potential miRNA-disease associations.

Chen X, Hua X, Jiang Z BMC Bioinformatics. 2021; 22(1):358.

PMID: 34215183 PMC: 8254275. DOI: 10.1186/s12859-021-04266-6.

Identification of infectious disease-associated host genes using machine learning techniques.

Barman R, Mukhopadhyay A, Maulik U, Das S BMC Bioinformatics. 2019; 20(1):736.

PMID: 31881961 PMC: 6935192. DOI: 10.1186/s12859-019-3317-0.

References

Altschul S, Madden T, Schaffer A, Zhang J, Zhang Z, Miller W . Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997; 25(17):3389-402. PMC: 146917. DOI: 10.1093/nar/25.17.3389. View

Laitinen T, Polvi A, Rydman P, Vendelin J, Pulkkinen V, Salmikangas P . Characterization of a common susceptibility locus for asthma-related traits. Science. 2004; 304(5668):300-4. DOI: 10.1126/science.1090010. View

Wjst M, Fischer G, Immervoll T, Jung M, Saar K, Rueschendorf F . A genome-wide search for linkage to asthma. German Asthma Genetics Group. Genomics. 1999; 58(1):1-8. DOI: 10.1006/geno.1999.5806. View

Tanahashi H, Tabira T . Genomic organization of the human X11L2 gene (APBA3), a third member of the X11 protein family interacting with Alzheimer's beta-amyloid precursor protein. Neuroreport. 1999; 10(12):2575-8. DOI: 10.1097/00001756-199908200-00025. View

Yokouchi Y, Nukaga Y, Shibasaki M, Noguchi E, Kimura K, Ito S . Significant evidence for linkage of mite-sensitive childhood asthma to chromosome 5q31-q33 near the interleukin 12 B locus by a genome-wide search in Japanese families. Genomics. 2000; 66(2):152-60. DOI: 10.1006/geno.2000.6201. View

Nyholt D . All LODs are not created equal. Am J Hum Genet. 2000; 67(2):282-8. PMC: 1287176. DOI: 10.1086/303029. View

Ober C, Tsalenko A, Parry R, Cox N . A second-generation genomewide screen for asthma-susceptibility alleles in a founder population. Am J Hum Genet. 2000; 67(5):1154-62. PMC: 1288558. DOI: 10.1016/S0002-9297(07)62946-2. View

Xu J, Postma D, Howard T, Koppelman G, Zheng S, Stine O . Major genes regulating total serum immunoglobulin E levels in families with asthma. Am J Hum Genet. 2000; 67(5):1163-73. PMC: 1288559. DOI: 10.1086/321190. View

Dizier M, Besse-Schmittler C, Guilloud-Bataille M, Annesi-Maesano I, Boussaha M, Bousquet J . Genome screen for asthma and related phenotypes in the French EGEA study. Am J Respir Crit Care Med. 2000; 162(5):1812-8. DOI: 10.1164/ajrccm.162.5.2002113. View

10.

Peltonen L, MCKUSICK V . Genomics and medicine. Dissecting human disease in the postgenomic era. Science. 2001; 291(5507):1224-9. DOI: 10.1126/science.291.5507.1224. View

11.

Laitinen T, Daly M, Rioux J, Kauppi P, Laprise C, Petays T . A susceptibility locus for asthma-related traits on chromosome 7 revealed by genome-wide scan in a founder population. Nat Genet. 2001; 28(1):87-91. DOI: 10.1038/ng0501-87. View

12.

Altmuller J, Palmer L, Fischer G, Scherb H, Wjst M . Genomewide scans of complex human diseases: true linkage is hard to find. Am J Hum Genet. 2001; 69(5):936-50. PMC: 1274370. DOI: 10.1086/324069. View

13.

Tabor H, Risch N, Myers R . Candidate-gene approaches for studying complex genetic traits: practical considerations. Nat Rev Genet. 2002; 3(5):391-7. DOI: 10.1038/nrg796. View

14.

Kent W, Sugnet C, Furey T, Roskin K, Pringle T, Zahler A . The human genome browser at UCSC. Genome Res. 2002; 12(6):996-1006. PMC: 186604. DOI: 10.1101/gr.229102. View

15.

Perez-Iratxeta C, Bork P, Andrade M . Association of genes to genetically inherited diseases using data mining. Nat Genet. 2002; 31(3):316-9. DOI: 10.1038/ng895. View

16.

Van Eerdewegh P, Little R, Dupuis J, Mastro R, Falls K, Simon J . Association of the ADAM33 gene with asthma and bronchial hyperresponsiveness. Nature. 2002; 418(6896):426-30. DOI: 10.1038/nature00878. View

17.

Freudenberg J, Propping P . A similarity-based method for genome-wide prediction of disease-relevant human genes. Bioinformatics. 2002; 18 Suppl 2:S110-5. DOI: 10.1093/bioinformatics/18.suppl_2.s110. View

18.

Pruitt K, Tatusova T, Maglott D . NCBI Reference Sequence project: update and current status. Nucleic Acids Res. 2003; 31(1):34-7. PMC: 165558. DOI: 10.1093/nar/gkg111. View

19.

van Driel M, Cuelenaere K, Kemmeren P, Leunissen J, Brunner H . A new web-based data mining tool for the identification of candidate genes for human genetic disorders. Eur J Hum Genet. 2003; 11(1):57-63. DOI: 10.1038/sj.ejhg.5200918. View

20.

Lohmueller K, Pearce C, Pike M, Lander E, Hirschhorn J . Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet. 2003; 33(2):177-82. DOI: 10.1038/ng1071. View