Using Classical Algorithms for Modern Applications: MCMC for Tail Calculations, EM - Lecture

Explore classical algorithms applied to modern challenges in this 29-minute lecture from the Computational Genomics Summer Institute. Delve into the use of Markov Chain Monte Carlo (MCMC) for tail probability calculations and Expectation-Maximization (EM) for PET reconstruction. Examine the incorporation of random coincidences in EM-based PET imaging reconstruction and techniques for estimating small tail probabilities using MCMC and Importance Sampling. Gain insights from related research papers, including works on efficient p-value evaluation for resampling-based tests and maximum likelihood reconstruction for emission tomography. Discover how these established methodologies are being adapted and applied to solve contemporary problems in computational genomics and medical imaging.