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The Protein Folding Problem and Tertiary Structure Prediction

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Cover of 'The Protein Folding Problem and Tertiary Structure Prediction'

Table of Contents

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    Book Overview
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    Chapter 1 Modeling Side Chains in Peptides and Proteins with the Locally Enhanced Sampling/Simulated Annealing Method
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    Chapter 2 Conformation Searching Using Simulated Annealing
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    Chapter 3 Multiple-Start Monte Carlo Docking of Flexible Ligands
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    Chapter 4 The Genetic Algorithm and Protein Tertiary Structure Prediction
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    Chapter 5 Conformational Search and Protein Folding
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    Chapter 6 Building Protein Folds Using Distance Geometry: Towards a General Modeling and Prediction Method
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    Chapter 7 Molecular Dynamics Studies of Protein and Peptide Folding and Unfolding
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    Chapter 8 Contact Potential for Global Identification of Correct Protein Folding
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    Chapter 9 Neural Networks for Molecular Sequence Classification
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    Chapter 10 The “Dead-End Elimination” Theorem: A New Approach to the Side-Chain Packing Problem
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    Chapter 11 Short Structural Motifs: Definition, Identification, and Applications
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    Chapter 12 In Search of Protein Folds
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    Chapter 13 An Adaptive Branch-and-Bound Minimization Method Based on Dynamic Programming
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    Chapter 14 Computational Complexity, Protein Structure Prediction, and the Levinthal Paradox
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    Chapter 15 Toward Quantitative Protein Structure Prediction
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    Chapter 16 The Role of Interior Side-Chain Packing in Protein Folding and Stability
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Title
The Protein Folding Problem and Tertiary Structure Prediction
Published by
Birkhäuser Boston, December 2012
DOI 10.1007/978-1-4684-6831-1
ISBNs
978-1-4684-6833-5, 978-1-4684-6831-1
Editors

Merz, Kenneth M., Grand, Scott M.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 36%
Researcher 3 21%
Student > Bachelor 1 7%
Unknown 5 36%
Readers by discipline Count As %
Computer Science 3 21%
Biochemistry, Genetics and Molecular Biology 2 14%
Agricultural and Biological Sciences 2 14%
Chemistry 2 14%
Unknown 5 36%