Abstract: Immune system is a network of cells, tissues, and organs that work together to defend the body against attacks by foreign invaders. Self/nonself discrimination ability based on the pattern recognition of molecular is a key feature in the defense of the host organism. T and B lymphocytes (we also call them T cells and B cells respectively) are two main types of immune cells which play principal roles in immune response. They express receptors on their surfaces to determine a given antigen. In this paper, we use metaphors extracted from natural immune systems and propose an artificial immune system model by considering both T cells dependent antigen recognition and T cells independent antigen recognition. We illustrate the ability of the proposed model in clustering analog patterns and recognizing noisy binary patterns. Simulation results are presented in support of the model and compared the results with that of other artificial immune models.