Bioinformatics Seminars

Bioinformatics Seminar

Time:
Venue: Na

15 March 2016

Na

Identification of novel therapeutics for complex diseases from genome-wide association data

Merridee Wouters
Olivia Newton-John Cancer Research Institute

Candidate gene prediction systems identify genes likely to be of functional relevance to a phenotype from associated genetic loci. Gentrepid ; a human candidate gene discovery platform ; utilizes several algorithms to enhance genotype-phenotype data using the biological knowledgebase: specifically information on molecular pathways ; protein-protein interactions ; domain function and transcriptional control regions (George et al ; 2006).

Recently ; we developed several protocols to analyse Genome-Wide Association Study (GWAS) data on complex diseases using the Wellcome Trust Case Control Consortium (WTCCC) data set on 7 complex diseases as an example (Ballouz et al ; 2011). This work demonstrated the biological knowledgebase can effectively enhance noisy GWAS data provided the effects of genomic architecture are taken into account. At present ; we are integrating drug databases to enable researchers to immediately associate potential therapeutics with candidate genes (Grover et al 2014). A more recent analysis of data on coronary artery disease will also be presented.




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