Topic: bipolar disorder

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used bioinformatics method that defines gene clusters (modules) based on correlated expression levels, allowing users to study relationships between modules, define groups of genes subserving common biological functions, and compare network topologies across distinct sets of expression data. WGCNA overcomes many challenges of gene-based studies, but it remains difficult to compare WGCNA results across studies, since gene modules are highly dependent on user parameters, experimental conditions, and other variables. As such, no con

Genome-wide association studies (GWAS) have identified multiple disease-associated genetic variations across different psychiatric disorders raising the question of how these genetic variants relate to the corresponding pharmacological treatments. In this talk, I will outline our work investigating whether functional information from a range of open bioinformatics datasets such as protein interaction network (PPI), brain eQTL, and gene expression pattern across the brain can uncover the relationship between GWAS-identified genetic variation and the genes targeted by current drugs for psychiatr