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FROM STATISTICAL PHYSICS TO DATA-DRIVEN MODELLING: with Applications to Quantitative Biology
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"From Statistical Physics to Data-Driven Modelling: with Applications to Quantitative Biology," authored by Francesco Zamponi, Remi Monasson, and Simona Cocco, is a groundbreaking exploration that seamlessly integrates the principles of statistical physics with cutting-edge data-driven modeling techniques, primarily applied to the realm of quantitative biology.
This comprehensive book goes beyond traditional boundaries, offering a bridge between theoretical physics and the emerging field of quantitative biology. It covers topics such as network theory, machine learning, and stochastic processes, providing a unified framework for understanding complex biological systems. With a focus on real-world applications and case studies, the authors demonstrate how statistical physics can be leveraged to address challenges in quantitative biology, from understanding cellular processes to decoding intricate biological networks.
This essential resource serves as a guide for researchers and students alike, facilitating a deep understanding of the interdisciplinary approach that combines statistical physics principles with advanced modeling methodologies to unravel the mysteries of quantitative biology. Aimed at graduate students, this textbook examines the importance of data analysis to understanding biological, physical, and chemical systems, and outlines its practical applications at the intersection of probability theory, statistics, optimisation, statistical physics, inference, and machine learning.

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