Identification of Significant Protein Diabetes Mellitus Type 2 with Fuzzy C- Means and Topological Analysis

Computational approach for identifying significance of proteins related to a certain disease was proposed as one of the solutions from the problem of experimental method application which is generally cost and time consuming. The case of study was conducted on diabetes mellitus (DM) type 2 disease. The purpose of this research is to identify significant proteins that causes diabetes mellitus type 2 by applying Fuzzy C-Means clustering algorithm and topological analysis from graph theory. A total of 100 proteins were obtained, some of them were identified as most significant proteins such as GCK, HNF4A, SLC30A8, SLC2A2, NEUROD1, PPARG, IRS1, HNF1B, PDX1 and RETN. It is expected that this results can be used by pharmacology researcher to screen the candidates of active compounds that have association with those proteins that representing diabetes mellitus (DM) type 2 disease.