BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is one of the most frequent diseases with monogenic inheritance. Previous data indicated that the heterozygous form occurred in 1:250 people. Based on these reports, around 36,000-40,000 people ...
MOTIVATION: Most gene prioritization methods model each disease or phenotype individually, but this fails to capture patterns common to several diseases or phenotypes. To overcome this limitation, we formulate the gene prioritization task as the fact...
Polycystic ovarian syndrome (PCOS) is an endocrine metabolic disorder with unclear etiopathogenesis among reproductive age women. Evidences show genetic susceptibility and environmental factors were associated with PCOS. The aim of this study was to ...
BACKGROUND: The inflammatory bowel diseases (IBDs) are chronic inflammatory disorders, associated with genetic, immunologic, and environmental factors. Although hundreds of genes are implicated in IBD etiology, it is likely that additional genes play...
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2017
Owing to the innate noise in the biological data sources, a single source or a single measure do not suffice for an effective disease gene prioritization. So, the integration of multiple data sources or aggregation of multiple measures is the need of...
BRCA Gist is an Intelligent Tutoring System that helps women understand issues related to genetic testing and breast cancer risk. In two laboratory experiments and a field experiment with community and web-based samples, an avatar asked 120 participa...
BACKGROUND: Discovery and incorporation of biomarker panels to cancer studies enabled the understanding of genetic variation and its interference in carcinogenesis at molecular level. The potential association between single nucleotide polymorphism (...
Journal of psychiatry & neuroscience : JPN
Sep 1, 2015
BACKGROUND: Brain imaging is of limited diagnostic use in psychiatry owing to clinical heterogeneity and low sensitivity/specificity of between-group neuroimaging differences. Machine learning (ML) may better translate neuroimaging to the level of in...