CHDbase: A Comprehensive Knowledgebase for Congenital Heart Disease-related Genes and Clinical Manifestations.

Congenital heart disease (CHD) is one of themost common causes of major birth defects, with a prevalence of 1%. Although an increasing number of studies have reported the etiology of CHD, the findings scattered throughout the literature are difficult to retrieve and utilize in research and clinical practice. We therefore developed CHDbase, an evidence-based knowledgebase of CHD-related genes and clinical manifestations manually curated from 1114 publications, linking 1124susceptibility genes and 3591 variations to more than 300 CHD types and related syndromes. Metadata such as the information of each publication and the selected population and samples, the strategy of studies, and the major findings of studies were integrated with each item of the research record. We also integrated functional annotations through parsing ∼ 50 databases/tools to facilitate the interpretation of these genes and variations in disease pathogenicity. We further prioritized the significance of these CHD-related genes with a gene interaction network approach and extracted a core CHD sub-network with 163 genes. The clear genetic landscape of CHD enables the phenotype classification based on the shared genetic origin. Overall, CHDbase provides a comprehensive and freely available resource to study CHD susceptibilities, supporting a wide range of users in the scientific and medical communities. CHDbase is accessible at http://chddb.fwgenetics.org.

Simplifying Weighted Heterogeneous Networks by Extracting h-Structure via s-Degree.

In this study, we developed a method to extract the core structure of weighted heterogeneous networks by transforming the heterogeneous networks into homogeneous networks. Using the standardized z-score, we define the s-degree by summing all the z-scores of adjacent edges into base-nodes for a weighted heterogeneous network. Then, we rank all the s-degrees in decreasing order to obtain the core structure via the h-index of a base-homogeneous-network. After reducing all adjacent edges between the attribute nodes and base-nodes to the core structure, we obtain the heterogeneous core structure of the weighted network, which is called the h-structure. We find that the h-structure in a heterogeneous network contains less than 1% nodes and edges, which results in the construction of a highly effective simplification of a weighted heterogeneous network. Two practical cases, the citation network and the co-purchase network, were examined in this study.