Models and Algorithms for Biomolecules and Molecular Networks

by Jie Liang, Bhaskar Dasgupta

By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms.Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms Sampling techniques for estimating evolutionary rates and generating molecular structures Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations End-of-chapter exercises

272 pages, Kindle Edition

First published December 25, 2012

Reviews

[Kelli Daniels-Richard]

Models and Algorithms for Biomolecules and Molecular Networks is an authoritative and highly detailed reference that provides a comprehensive view of computational approaches to understanding biological systems. Jie Liang and Bhaskar Dasgupta skillfully combine theory, modeling frameworks, algorithms, and practical exercises to give readers both conceptual understanding and hands-on problem-solving skills.

What stands out most is the clarity with which complex topics are presented. From sampling techniques for evolutionary rates to the computation of stochastic network probabilities, the book balances theoretical rigor with practical application, making it a valuable resource for students and researchers alike.

My favorite element is the inclusion of end-of-chapter exercises and open problems, which invite readers to engage actively with the material and test their understanding. Models and Algorithms for Biomolecules and Molecular Networks is a must-have reference for anyone seeking to explore computational biology and systems modeling with depth and precision.