THD-Tricluster method on gene expression data of multiple sclerosis patients receiving interferon-beta therapy

Abstract

THD-Tricluster method is a triclustering analysis with a biclustering-based approach. The THD-Tricluster method uses the Shifting-and-Scaling Similarity (SSSim) value to form a bicluster first and shows it by forming a tricluster. The SSSim value uses Shifting-and-Scaling Correlation to use an interface with shifting and scaling patterns as well as intertemporal coherence and compares it with the threshold value. THD-Tricluster method was performed on treatment response data to interferon-beta therapy in multiple sclerosis patients. The optimal scenario is a scenario with a coverage value scenario that uses the highest threshold value. In this scenario, there are two types of tricluster, namely the tricluster which has a collection of genes in responsive patients and patients who are not responsive to therapy. The differences collection of genes in both tricluster can be used by medical professionals in the development of interferon-beta therapy treatments to create a therapy response on multiple sclerosis disease.