NLRP10 is one of the members of NOD-like receptors (NLRs) family that is least characterized. It is a protein that takes part in pathogen sensing and responsible for the subsequent signaling propagation leading to immunologic response. In this study, computational tools such as algorithm, web server and database were used to investigate the domain of NLRP10 protein. The findings of this research may provide computational insights into the structure and functions of NLRP10, which in turn may foster better understanding of the role of NLRP10 in the immunologic defense.

Exponential accumulation of biological data requires computer scientists and bioinformaticians to improve the efficiency of computer algorithms and databases. The recent advancement of computational tools has boosted the processing capacity of enormous volume of genetic data. This research applied a computational approach to analyze the tandem repeat patterns in Nlrc4 gene. Because the protein product of Nlrc4 gene is important in detecting pathogen and triggering subsequent immune responses, the results of this genetic analysis is essential for the understanding of the genetic characteristics of Nlrc4. The study on the distribution of tandem repeats may provide insights for drug design catered for the Nlrc4-implicated diseases.