Affiliation: Radboud University Nijmegen
Country: The Netherlands
- Gentrepid V2.0: a web server for candidate disease gene predictionSara Ballouz
School of Medicine, Deakin University, Geelong, VIC 3217, Australia
BMC Bioinformatics 14:249. 2013..As experimental studies detecting associations between genetic intervals and disease proliferate, better bioinformatic techniques that can expand and exploit the data are required...
- Conserved co-expression for candidate disease gene prioritizationMartin Oti
Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Geert Grooteplein 26 28, 6525 GA, Nijmegen, The Netherlands
BMC Bioinformatics 9:208. 2008..Here we examine whether co-expression across multiple species is also a better prioritizer of disease genes than is co-expression between human genes alone...
- Web tools for the prioritization of candidate disease genesMartin Oti
Structural and Computational Biology Division, Victor Chang Cardiac Research Institute, 2010, Darlinghurst, NSW, Australia
Methods Mol Biol 760:189-206. 2011..In this chapter, we give an overview of computational tools that can be used for this purpose, all of which are freely available over the web...
- The biological coherence of human phenome databasesMartin Oti
Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Geert Grooteplein 26 28, 6525 GA Nijmegen, The Netherlands
Am J Hum Genet 85:801-8. 2009..More generally, we propose that curation and more systematic annotation of human phenome databases can greatly improve the power of the phenotype for genetic disease analysis...
- Analysis of genome-wide association study data using the protein knowledge baseSara Ballouz
Structural and Computational Biology Division, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
BMC Genet 12:98. 2011..A major benefit of multi-locus comparison is that it compensates for some shortcomings of current statistical analyses that test the frequency of each SNP in isolation for the phenotype population versus control...
- Phenome connectionsMartin Oti
Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Nijmegen, The Netherlands
Trends Genet 24:103-6. 2008..Their results imply that the human phenome can be viewed as a landscape of interrelated diseases, reflecting overlapping molecular causation...
- Prediction of human disease genes by human-mouse conserved coexpression analysisUgo Ala
Molecular Biotechnology Center, Department of Genetics, Biology and Biochemistry, University of Turin, Turin, Italy
PLoS Comput Biol 4:e1000043. 2008..However, so far, gene coexpression has not been used very successfully to prioritize positional candidates...
- Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genesNicki Tiffin
South African National Bioinformatics Institute, University of the Western Cape, Bellville, 7535, South Africa
Nucleic Acids Res 34:3067-81. 2006..Two genes, LPL and BCKDHA, are common to these two sets. We also present a set of secondary candidates for T2D (94 genes) and for obesity (116 genes) with 58 genes in common to both diseases...
- Conservation of divergent transcription in fungiPhilip R Kensche
Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Center, 6500 HB Nijmegen, The Netherlands
Trends Genet 24:207-11. 2008..The functional interactions of the proteins encoded by the conserved divergent gene pairs indicate a potential for protein function prediction in eukaryotes...