The GeneWeaver bipartite data model provides an efficient means to evaluate shared molecular components from sets derived across diverse species, disease states and biological processes. In order to adapt this model for examining related molecular components and biological networks, such as pathway or gene network data, we have developed a means to leverage the bipartite data structure to extract and analyze shared edges. Using the Pathway Commons database we demonstrate the ability to rapidly identify shared connected components among a diverse set of pathways. In addition, we illustrate how results from maximal bipartite discovery can be decomposed into hierarchical relationships, allowing shared pathway components to be mapped through various parent-child relationships to help visualization and discovery of emergent kernel driven relationships. Interrogating common relationships among biological networks and conventional GeneWeaver gene lists will increase functional specificity and reliability of the shared biological components. This approach enables self-organization of biological processes through shared biological networks.

36The role of the microbiome in health and disease involves complex networks of host genetics, 37 genomics, microbes and environment. Identifying the mechanisms of these interactions has 38 remained challenging. Systems genetics in the laboratory mouse enables data-driven discovery of 39 network components and mechanisms of host-microbial interactions underlying multiple disease 40 phenotypes. To examine the interplay among the whole host genome, transcriptome and 41 microbiome, we mapped quantitative trait loci and correlated the abundance of cecal mRNA, 42 luminal microflora, physiology and behavior in incipient strains of the highly diverse 43Collaborative Cross mouse population. The relationships that are extracted can be tested 44 experimentally to ascribe causality among host and microbe in behavior and physiology, 45 providing insight into disease. Application of this strategy in the Collaborative Cross population 46 revealed experimentally validated mechanisms of microbial involvement in models of autism, 47 inflammatory bowel disease and sleep disorder. 48

Behçet's disease (BD) is a multisystem inflammatory disease that effects patients along the historic silk road. Thus far, the patheogensis of the disease has proved elusive due to the complex genetic interactions and unknown environmental or viral triggering factors of the disease. In this paper, we seek to clarify the gentic factors of the disease while also uncovering other diseases of interest that present with a similar genotype as BD. To do this, we employ a computational functional genomics approach by leveraging the hierarchical similarity tool available in Geneweaver. Through our analysis, we were able to ascertain 7 BD consensus genes and 16 autoimmune diseases with genetic overlap with BD. The results of our study will inform further research into the patheogenesis of Behçet's Disease.