Inference on Biological Dynamics with Memory

Learn to analyze and infer biological systems that exhibit memory effects through advanced mathematical and computational approaches in this seminar presentation. Explore how memory influences biological dynamics across various scales, from molecular processes to population-level phenomena, and discover the theoretical frameworks needed to model these complex temporal dependencies. Examine specific case studies where memory plays a crucial role in biological systems, including cellular signaling pathways, neural networks, and ecological dynamics. Master the statistical inference techniques required to identify memory signatures in experimental data and understand how to distinguish between different types of memory mechanisms. Investigate the mathematical tools used to characterize memory kernels and their impact on system behavior, including fractional calculus and non-Markovian stochastic processes. Gain insights into the computational challenges associated with parameter estimation in memory-dependent models and learn about recent advances in inference algorithms designed for these systems. Understand the biological significance of memory effects and their evolutionary implications across different biological contexts.