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Computational Methods in Protein Evolution

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Cover of 'Computational Methods in Protein Evolution'

Table of Contents

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    Book Overview
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    Chapter 1 Predicting the Effect of Mutations on Protein Folding and Protein-Protein Interactions
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    Chapter 2 Accurate Calculation of Free Energy Changes upon Amino Acid Mutation
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    Chapter 3 Protocols for the Molecular Evolutionary Analysis of Membrane Protein Gene Duplicates
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    Chapter 4 Computational Prediction of De Novo Emerged Protein-Coding Genes
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    Chapter 5 Coevolutionary Signals and Structure-Based Models for the Prediction of Protein Native Conformations
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    Chapter 6 Detecting Amino Acid Coevolution with Bayesian Graphical Models
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    Chapter 7 Context-Dependent Mutation Effects in Proteins
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    Chapter 8 High-Throughput Reconstruction of Ancestral Protein Sequence, Structure, and Molecular Function
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    Chapter 9 Ancestral Sequence Reconstruction as a Tool for the Elucidation of a Stepwise Evolutionary Adaptation
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    Chapter 10 Enhancing Statistical Multiple Sequence Alignment and Tree Inference Using Structural Information
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    Chapter 11 The Influence of Protein Stability on Sequence Evolution: Applications to Phylogenetic Inference
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    Chapter 12 Navigating Among Known Structures in Protein Space
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    Chapter 13 A Graph-Based Approach for Detecting Sequence Homology in Highly Diverged Repeat Protein Families
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    Chapter 14 Exploring Enzyme Evolution from Changes in Sequence, Structure, and Function
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    Chapter 15 Identification of Protein Homologs and Domain Boundaries by Iterative Sequence Alignment
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    Chapter 16 A Roadmap to Domain Based Proteomics
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    Chapter 17 Modeling of Protein Tertiary and Quaternary Structures Based on Evolutionary Information
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    Chapter 18 Interface-Based Structural Prediction of Novel Host-Pathogen Interactions
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    Chapter 19 Predicting Functions of Disordered Proteins with MoRFpred
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    Chapter 20 Exploring Protein Conformational Diversity
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    Chapter 21 High-Throughput Antibody Structure Modeling and Design Using ABodyBuilder
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    Chapter 22 In Silico-Directed Evolution Using CADEE
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Title
Computational Methods in Protein Evolution
Published by
Springer New York, January 2019
DOI 10.1007/978-1-4939-8736-8
ISBNs
978-1-4939-8735-1, 978-1-4939-8736-8
Editors

Tobias Sikosek

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X Demographics

The data shown below were collected from the profiles of 19 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 127 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 21%
Researcher 25 20%
Student > Master 18 14%
Student > Bachelor 11 9%
Student > Doctoral Student 8 6%
Other 14 11%
Unknown 24 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 49 39%
Agricultural and Biological Sciences 19 15%
Chemistry 7 6%
Engineering 6 5%
Chemical Engineering 5 4%
Other 12 9%
Unknown 29 23%