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Disease Interactome: An Assessment Case Study Based on Analysis and Measures to Predict Secondary Diseases
Abstract
The disease interactome is a network of genes that are related to each other through some attributes. These genes, being part of various diseases, show a high correlation among many diseases. Genes being a major part of the interactome thus can be used to determine the relationship between various diseases, their symptoms, clinical similarity, and co-morbidity. Subgraphs and similarity factors such as Jaccardian distance, cosine similarities, and others have been exploited to calculate the relationship between two or more diseases. Many diseases that did not show much resemblance on the basis of gene similarity or symptom similarity were seen to be closely related according to network interactome. The quantitative analysis between disease-disease was also done. Clustering algorithms like hierarchical clustering involving single, complete, and average linkage were applied to get a visual representation in the form of a dendrogram. Thus, disease-disease interactome was created, analyzed for finding related secondary diseases, and their basic nature was understood.
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