Quantifying Randomness in Biological Data

This lecture introduces the concept of randomness and information in biological data, focusing on the quantification of randomness through discrete random variables. The instructor discusses the importance of thermal fluctuations at the cellular scale and the role of random walks in biological systems. The lecture also covers extracting information from biological data, including quantifying entropy, statistical dependence, and inferring probability distributions. Examples from neuroscience and protein sequence data are used to illustrate these concepts, emphasizing the application of inference, machine learning, and statistical physics in understanding biological processes.