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Computational Peptidology

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Cover of 'Computational Peptidology'

Table of Contents

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    Book Overview
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    Chapter 1 De Novo Peptide Structure Prediction: An Overview
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    Chapter 2 Molecular Modeling of Peptides
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    Chapter 3 Improved Methods for Classification, Prediction, and Design of Antimicrobial Peptides.
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    Chapter 4 Building MHC Class II Epitope Predictor Using Machine Learning Approaches
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    Chapter 5 Brownian Dynamics Simulation of Peptides with the University of Houston Brownian Dynamics (UHBD) Program
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    Chapter 6 Computational Prediction of Short Linear Motifs from Protein Sequences
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    Chapter 7 Peptide Toxicity Prediction
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    Chapter 8 Synthetic and Structural Routes for the Rational Conversion of Peptides into Small Molecules
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    Chapter 9 In Silico Design of Antimicrobial Peptides.
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    Chapter 10 Information-driven modeling of protein-Peptide complexes.
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    Chapter 11 Computational Approaches to Developing Short Cyclic Peptide Modulators of Protein–Protein Interactions
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    Chapter 12 A Use of Homology Modeling and Molecular Docking Methods: To Explore Binding Mechanisms of Nonylphenol and Bisphenol A with Antioxidant Enzymes
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    Chapter 13 Computational Peptide Vaccinology
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    Chapter 14 Computational Modeling of Peptide–Aptamer Binding
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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