Molecular Networking: Statistical Mechanics in AI and Machine Learning

Description

The book builds on the analogy between social groups and assemblies of molecules to introduce the concepts of statistical mechanics, machine learning and data science. Applying a data analytics approach to molecular systems, we show how individual (molecular) features and interactions between molecules, or “communication” processes, allow for the prediction of properties and collective behavior of molecular systems – just as polling and social networking shed light on the behavior of social groups. Applications to systems at the cutting-edge of research for biological, environmental, and energy applications are also presented.
Key features: Draws on a data analytics approach of molecular systems Covers hot topics such as artificial intelligence and machine learning of molecular trends Contains applications to systems at the cutting-edge of research for biological, environmental and energy applications Discusses molecular simulation and links with other important, emerging techniques and trends in computational sciences and society Authors have a well-established track record and reputation in the field