CardioGenBase: A Literature Based Multi-Omics Database for Major Cardiovascular Diseases.

Cardiovascular diseases (CVDs) account for high morbidity and mortality worldwide. Both, genetic and epigenetic factors are involved in the enumeration of various cardiovascular diseases. In recent years, a vast amount of multi-omics data are accumulated in the field of cardiovascular research, yet the understanding of key mechanistic aspects of CVDs remain uncovered. Hence, a comprehensive online resource tool is required to comprehend previous research findings and to draw novel methodology for understanding disease pathophysiology. Here, we have developed a literature-based database, CardioGenBase, collecting gene-disease association from Pubmed and MEDLINE. The database covers major cardiovascular diseases such as cerebrovascular disease, coronary artery disease (CAD), hypertensive heart disease, inflammatory heart disease, ischemic heart disease and rheumatic heart disease. It contains ~1,500 cardiovascular disease genes from ~2,4000 research articles. For each gene, literature evidence, ontology, pathways, single nucleotide polymorphism, protein-protein interaction network, normal gene expression, protein expressions in various body fluids and tissues are provided. In addition, tools like gene-disease association finder and gene expression finder are made available for the users with figures, tables, maps and venn diagram to fit their needs. To our knowledge, CardioGenBase is the only database to provide gene-disease association for above mentioned major cardiovascular diseases in a single portal. CardioGenBase is a vital online resource to support genome-wide analysis, genetic, epigenetic and pharmacological studies

The parameters used validate the database.

<p>Statistics were employed to find out the precision, recall, accuracy and F-measure of CardioGenBase. Overall, the results support the viability and quality of data represented in the database.</p

Text mining results.

<p>The number of literature collected for each cardiovascular disease. These literature was filtered based on title/abstract, relevance to the search terms to extract genes/proteins using a semi-automated method.</p

CardioGenBase Construction.

<p>The framework describes the construction of CardioGenBase. It includes data mining of biomolecules, filtration, curation, enrichment, system interface and visualization.</p

CVD Gene Finder.

<p>a) The literature evidence and molecular information could be obtained for a gene of interest. User can search the gene by HGNC ID or gene symbol. b) The output shows the molecular information on the query gene.</p

Disease Finder.

<p>a) All the reported genes associated a major cardiovascular disease could be retrieved using this query page. b) The result page showing all the genes associated with a disease of interest.</p

Gene Mapper.

<p>a) Multiple query genes can be searched at once. b) The result shows input list, disease gene as Venn diagram. Also, the number of articles for each query gene is provided.</p

Gene Expression Finder.

<p>a) This tool enables users to identify gene expression in various microarray experiments associated to cardiovascular disease condition. b) the result represented as a bar diagram where the raw intensities of grouped samples are given as interactive charts.</p

List of fifty genes selected by the volunteers for validation.

<p>These fifty genes were searched in CardioGenBase and CADgene database for effective comparison. The result shows that most of the cardiac genes are found in CardioGenBase than CADgene database.</p