According to the World Health Organization (WHO), over 1-3 million children under the age of five die due to malaria each year. The aim of this project is to increase our understanding of the Plasmodiumchabaudi parasite and of its interactions with the mammalian host using a computational approach. This is achieved by applying a time-series clustering algorithm to a publicly available short time-series gene expression data representing two disease states (P.chabaudi infected and non infected), two genders (male and female), two protocols (intact and gonadectomized), and four time points (0, 3, 7, and 14 days after inoculation) of Musmusculus (mouse) response to P.chabaudi infection. Results obtained provide a rigorous statistical explanation to the fact that intact males were more likely than intact females to die following P.chabaudi infection on one hand, and on the other hand, gonadectomy of male and female mice altered these sex-associated differences. These findings may suggest that sex steroid hormone modulates immune responses to pathogen attacks.