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Title
A Metaheuristic Approach to Protein Structure Prediction : Algorithms and Insights from Fitness Landscape Analysis / by Nanda Dulal Jana, Swagatam Das, Jaya Sil.
ISBN
9783319747750
3319747754
9783319747743
3319747746
Published
Cham : Springer International Publishing : Imprint: Springer, 2018.
Language
English
Description
1 online resource (xxix, 220 pages) : illustrations.
Item Number
10.1007/978-3-319-74775-0 doi
Call Number
Q342
Dewey Decimal Classification
572/.633
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Series
Emergence, complexity and computation ; 31.
Available in Other Form
Print version: 9783319747743
Metaheuristic Protein Structure Prediction-An Overview
Related Works
Continuous Landscape Analysis using Random Walk Algorithm
Landscape Characterization and Algorithms Selection for the PSP Problem
The Levy distributed Parameter Adaptive Metaheuristic Algorithm for Protein Structure Prediction
Protein Structure Prediction using Improved Variants of Metaheuristic Algorithms
Hybrid Metaheuristic Approach for Protein Structure Prediction
Conclusions and Future Research.
