Information analysis to study interactions between different genes and diseases

Protein and DNA features' extraction represents an interesting research subject for a wide range of relevant applications. In this paper, we studied different methods of grouping a large number of diseases and diseases based on some common attributes. Our goal is to study any patterns of information that can be extracted based on evaluating those diseases and genes in large groups. Input dataset is collected from public resources. We proposed and developed an algorithm to extract the total and weighted strengths in associating diseases with genes. The results showed that more than 88% of success rates in finding a real association between maximum clique genes which was verified manually.