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A Metaheuristic Approach to Protein Structure Prediction

Algorithms and Insights from Fitness Landscape Analysis

  • Book
  • © 2018

Overview

Authors:
  1. Nanda Dulal Jana

    1. Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur, India

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  2. Swagatam Das

    1. Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India

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  3. Jaya Sil

    1. Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Howrah, India

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  • Presents structural features of the protein-structure prediction (PSP) problem and well-known metaheuristic techniques
  • Introduces algorithms and insights from fitness landscape analysis
  • Demonstrates how to generate the protein landscape structure based on the sampling technique for determining the structural properties of the protein landscape

Part of the book series: Emergence, Complexity and Computation (ECC, volume 31)

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About this book

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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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xxix
    Download chapter PDF

  2. Backgrounds on Protein Structure Prediction and Metaheuristics

    • Nanda Dulal Jana, Swagatam Das, Jaya Sil
    Pages 1-28

  3. Metaheuristic Approach to PSP—An Overview of the Existing State-of-the-art

    • Nanda Dulal Jana, Swagatam Das, Jaya Sil
    Pages 29-38

  4. Continuous Landscape Analysis Using Random Walk Algorithm

    • Nanda Dulal Jana, Swagatam Das, Jaya Sil
    Pages 39-85

  5. Landscape Characterization and Algorithms Selection for the PSP Problem

    • Nanda Dulal Jana, Swagatam Das, Jaya Sil
    Pages 87-150

  6. The Lévy Distributed Parameter Adaptive Differential Evolution for Protein Structure Prediction

    • Nanda Dulal Jana, Swagatam Das, Jaya Sil
    Pages 151-167

  7. Protein Structure Prediction Using Improved Variants of Metaheuristic Algorithms

    • Nanda Dulal Jana, Swagatam Das, Jaya Sil
    Pages 169-195

  8. Hybrid Metaheuristic Approach for Protein Structure Prediction

    • Nanda Dulal Jana, Swagatam Das, Jaya Sil
    Pages 197-206

  9. Conclusions and Future Research

    • Nanda Dulal Jana, Swagatam Das, Jaya Sil
    Pages 207-209

  10. Back Matter

    Pages 211-220
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Authors and Affiliations

  • Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur, India

    Nanda Dulal Jana

  • Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India

    Swagatam Das

  • Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Howrah, India

    Jaya Sil

About the authors


Bibliographic Information

  • Book Title: A Metaheuristic Approach to Protein Structure Prediction

  • Book Subtitle: Algorithms and Insights from Fitness Landscape Analysis

  • Authors: Nanda Dulal Jana, Swagatam Das, Jaya Sil

  • Series Title: Emergence, Complexity and Computation

  • DOI: https://doi.org/10.1007/978-3-319-74775-0

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2018

  • Hardcover ISBN: 978-3-319-74774-3Published: 16 March 2018

  • Softcover ISBN: 978-3-030-09075-3Published: 22 December 2018

  • eBook ISBN: 978-3-319-74775-0Published: 05 March 2018

  • Series ISSN: 2194-7287

  • Series E-ISSN: 2194-7295

  • Edition Number: 1

  • Number of Pages: XXIX, 220

  • Number of Illustrations: 5 b/w illustrations, 54 illustrations in colour

  • Topics: Computational Intelligence, Complexity, Artificial Intelligence, Protein Structure

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