Sequential Bayesian inference (SBI) offers an attractive data assimilation framework for uncertainty quantification of biological systems with temporal dynamics. In this talk, I will give an overview of SBI methods and their use in solving nonstationary inverse problems characterized by dynamical systems, emphasizing novel applications in biology and biomedical engineering, including recent work identifying tissue physical properties for laser surgery.