For bioinformaticians, computational biologists, and wet-lab biologists, the authors provide the latest machine learning approaches for protein subcellular localization prediction with a systemic scheme for improving predictors performance.
Part 1. Introducing probabilistic programming. 1. Probabilistic programming in a nutshell -- 2. A quick Figaro tutorial -- 3. Creating a probabilistic programming application -- 4. Probabilistic models and probabilistic programs -- 5. Modeling dependencies with Bayesian and Mark…
"Probabilistic programming is a programming paradigm in which code models are used to draw probabilistic inferences from data. By applying specialized algorithms, programs assign degrees of probability to conclusions and make it possible to forecast future events like sales tren…
