Titlebook: Computational Methods in Protein Evolution; Tobias Sikosek Book 2019 Springer Science+Business Media, LLC, part of Springer Nature 2019 ph

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2.2.1.2.6-7 References for 2.2.1.2,web server that is freely available at .. We describe this predictor, explain how to run the web server, and show how to interpret the results it generates. We also demonstrate the utility of this web server based on two case studies, focusing on the relevance of evolutionary conservation of MoRF regions.

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2.2.1.2.6-7 References for 2.2.1.2,ng the protein-coding sequences. Here we describe a machine learning method (Bayesian graphical models) implemented in the open-source phylogenetic software package ., ., for extracting a network of coevolving residues from a sequence alignment.

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Book 2019reproducible computational protocols (using command line or graphical user interfaces, sometimes including computer code), and tips on troubleshooting and avoiding known pitfalls..Cutting-edge and authoritative, .Computational Methods in Protein Evolution. is a valuable resource that offers useful w

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Coevolutionary Signals and Structure-Based Models for the Prediction of Protein Native Conformationnctional amino acid chain. In this chapter, we introduce a general and efficient methodology to perform coevolutionary analysis on protein sequences and to use this information in combination with computational physical models to predict the native 3D conformation of functional polypeptides. We pres