Performing the comparative analysis to understand the functional roles of genes in different pathways of cardiomyopathy disease

Personalized medicine is one of the popular approaches in biological sciences. Due to the great attention in personalized medicine, there exists a need for health decision algorithms developed through high-level programming languages that already compromised the statistical analyses and numerical computations. Here, we present a tool that enables us to facilitate making research in the PubMed database by classifying the scientific literature from the published abstracts and then performed the comparative analysis to highlight the importance of gene-variant relationships in the decision steps. After retrieving related genes from literature, we performed pathway analysis with them by using computer-based tools to differentiate these sub-pathways in cardiomyopathy disease that are listed as hypertrophic, dilated, and arrhythmogenic right ventricular cardiomyopathy. Then, the pathogenic variants existing in these genes at each sub-pathway are retrieved, and the mechanistic interpretation about them has been gained to explain more about the differences in genes' mode of action. Lastly, the need of structure-based studies to explain the etiology of the disease has been emphasized by providing the protein structures of related genes as a guide. This study presents the importance of combining the text-mining approach with the bioinformatics tool in effective manner both for catching up with the updated literature and for revealing newly identified genes or pathways.