Models and Algorithms for Biomolecules and Molecular Networks - IEEE Press Biomedical Engineering by Bhaskar Dasgupta & Jie Liang Hardcover

Book Synopsis

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

From the Back Cover

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.

Models and Algorithms for Biomolecules and Molecular Networks begins by covering areas of structural and geometric models of biomolecules and their shape characterization. The first topic discussed is protein geometry, including voids and pockets and how to effectively use them to infer and characterize biological functions of proteins. Scoring functions for predicting structures and binding proteins, using both statistical analysis and optimization techniques are then discussed, followed by the development of sampling techniques for conformation of biomolecules and protein evolution.

The second part of the book covers interaction networks of biomolecules. Topics include stochastic models for networks with small copy numbers of molecular species, signal transduction networks, and biological models in the framework of dynamic systems. In the final chapter, dynamical and topological properties of specific biological models are discussed, as well as their salient features, which make them attractive in their applications.

Special features of this book include:

• 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

This book will equip readers with the necessary background knowledge and skillset to solve practical problems and carry out research for future advancements in the field.

About the Author

BHASKAR DASGUPTA is a Professor in the Computer Science department at the University of Illinois at Chicago, USA. He has written numerous bioinformatics research papers. Dr. DasGupta was the recipient of the NSF CAREER award in 2004 and the UIC College of Engineering Faculty Teaching award in 2012.

JIE LIANG is the Richard and Loan Hill Professor within the Department of Bioengineering and Department of Computer Science at the University of Illinois at Chicago, USA. He earned his Ph.D. in Biophysics. He was an NSF CISE postdoctoral research associate (1994-1996) at the Beckman Institute and National Center for Supercomputing and its Applications (NCSA), as well as a visiting fellow at the NSF Institute of Mathematics and Applications at Minneapolis. He was a recipient of the NSF CAREER award in 2003. He was elected a fellow of the American Institute of Medicine and Biological Engineering in 2007. He was a University Scholar (2010-2012).