In this talk, I will present our recent work in trying to understand bacterial chemotaxis (bacteria’s ability to sense and track chemical gradient) by using a quantitative modeling approach. Based on molecular level knowledge of the E. coli chemotaxis pathway, we propose a simple model for bacterial chemotaxis and use it to address several interesting, important system-level questions: 1) What kind of computation does a E. coli cell perform in response to complex time-varying stimuli? 2) What kind of memory does E. coli have? How long does it take the cell to forget? 3) How does the cell use its memory and computation capability to sense and respond to a minute chemical gradient (food or poison) among a wide range of background.