Monte Carlo Methods in Biology and Medicine

Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to obtain numerical results. They are increasingly influential in biology and medicine. These methods are utilized to model complex biological systems and predict outcomes where analytical solutions are impractical. In genomics, Monte Carlo simulations help in understanding genetic variation and evolutionary processes by simulating random genetic drift and mutation effects over generations. In epidemiology, these methods are used to predict the spread of infectious diseases by modeling various scenarios of transmission and intervention strategies, aiding public health decision-making. In medical imaging, particularly in techniques like PET (Positron Emission Tomography) and SPECT (Single Photon Emission Computed Tomography), Monte Carlo simulations are used to model the transport of photons through tissues, improving image reconstruction and accuracy. This book elucidates the concepts and innovative models around prospective developments with respect to Monte Carlo methods. The topics included herein are of utmost significance and bound to provide incredible insights to readers. The readers would gain knowledge that would broaden their perspective about computer algorithms based on Monte Carlo method.