A Metaheuristic Approach to Protein Structure Prediction: Algorithms and Insights from Fitness Landscape Analysis: 31 (Emergence, Complexity and Computation, 31)

A Metaheuristic Approach to Protein Structure Prediction:Algorithms and Insights from Fitness Landscape Analysis:31 (Emergence, Complexity and Computation, 31)

A Metaheuristic Approach to Protein Structure Prediction:Algorithms and Insights from Fitness Landscape Analysis:31 (Emergence, Complexity and Computation, 31)

by: Nanda Dulal Jana (Author), Swagatam Das (Author),Jaya Sil (Author)

Publisher: Springer

Edition: 1st ed. 2018

Publication Date: 2018-03-16

Language: English

Print Length: 249 pages

ISBN-10: 3319747746

ISBN-13: 9783319747743

Book Description

This book introduces characteristic features of the protein structure prediction (PSP) problem. It focuses on systematic selection and improvement of the most appropriate metaheuristic algorithm to solve the problem based on a fitness landscape analysis, rather than on the nature of the problem, which was the focus of methodologies in the past. Protein structure prediction is concerned with the question of how to determine the three-dimensional structure of a protein from its primary sequence. Recently a number of successful metaheuristic algorithms have been developed to determine the native structure, which plays an important role in medicine, drug design, and disease prediction. This interdisciplinary book consolidates the concepts most relevant to protein structure prediction (PSP) through global non-convex optimization. It is intended for graduate students from fields such as computer science, engineering, bioinformatics and as a reference for researchers and practitioners.

Editorial Reviews

This book introduces characteristic features of the protein structure prediction (PSP) problem. It focuses on systematic selection and improvement of the most appropriate metaheuristic algorithm to solve the problem based on a fitness landscape analysis, rather than on the nature of the problem, which was the focus of methodologies in the past. Protein structure prediction is concerned with the question of how to determine the three-dimensional structure of a protein from its primary sequence. Recently a number of successful metaheuristic algorithms have been developed to determine the native structure, which plays an important role in medicine, drug design, and disease prediction. This interdisciplinary book consolidates the concepts most relevant to protein structure prediction (PSP) through global non-convex optimization. It is intended for graduate students from fields such as computer science, engineering, bioinformatics and as a reference for researchers and practitioners.

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