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,dependently of each other and under the same substitution process. However, it is well known that the structural properties of a protein site in the native state affect its evolution, in particular the sequence entropy and the substitution rate. Starting from the seminal proposal by Halpern and Brun

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parsimony

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2.2.1.2.6-7 References for 2.2.1.2,et of domains into unique arrangements, a large number of distinct proteins can be generated. Since domains often have specific functions, changes in their arrangement usually affect the overall protein function. Furthermore, domains are well amenable to computational representations, e.g., by Hidde

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2.3.2.5 Presentation of results,ucture of a protein is therefore instrumental to gain information about the molecular basis of its function. However, experimental structure determination is inherently time consuming and expensive, making it impossible to follow the explosion of sequence data deriving from genome-scale projects. As

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2.2.1.2.6-7 References for 2.2.1.2,ns. Molecular recognition features (MoRFs) are segments of intrinsically disordered regions that bind to partner proteins, where binding is concomitant with a transition to a structured conformation. MoRFs facilitate translation, transport, signaling, and regulatory processes and are found across al

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https://doi.org/10.1007/978-1-4939-8736-8phylogenetic trees; sequence reconstruction; co-evolution; Epistasis; allostery

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978-1-4939-9378-9Springer Science+Business Media, LLC, part of Springer Nature 2019