Название: Molecular Networking: Statistical Mechanics in the Age of AI and Machine Learning
Автор: Caroline Desgranges, Jerome Delhommelle
Издательство: CRC Press
Год: 2024
Страниц: 249
Язык: английский
Формат: pdf (true)
Размер: 26.8 MB
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. Social networks, Machine Learning, and Artificial Intelligence (AI) have become part of our daily lives. We live in an era where data analysis is present in all aspects of society and a driving force for many decisions that impact our present and future. While statistics have long played a significant role in numbers-driven domains, the development of novel machine learning algorithms, combined with the increase in computing performance and data storage, has led to a paradigm shift in how we approach and address challenges. For instance, in human health, the concept of precision medicine, which considers the individual features of a patient, has emerged as a promising alternative to one-size-fits-all medical treatments. Similarly, the sampling of opinion through polling methods had been for decades a staple of, for example, commercial and political analyses. It is now complemented by the analysis of data from social networks, which provide a window into human interactions and the interrelation between individual and collective responses.
