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Predicting protein–protein interactions in the context of protein evolution

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TLDR
The evolutionary assumptions implicit in many of the protein interaction prediction methods are elucidated and the caution needed in deploying certain evolutionary assumptions is drawn, in particular cross-organism transfer of interactions by sequence homology.
Abstract
Here we review the methods for the prediction of protein interactions and the ideas in protein evolution that relate to them. The evolutionary assumptions implicit in many of the protein interaction prediction methods are elucidated. We draw attention to the caution needed in deploying certain evolutionary assumptions, in particular cross-organism transfer of interactions by sequence homology, and discuss the known issues in deriving interaction predictions from evidence of co-evolution. We also conject that there is evolutionary knowledge yet to be exploited in the prediction of interactions, in particular the heterogeneity of interactions, the increasing availability of interaction data from multiple species, and the models of protein interaction network growth.

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Citations
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Journal ArticleDOI

STRING v10: protein–protein interaction networks, integrated over the tree of life

TL;DR: H hierarchical and self-consistent orthology annotations are introduced for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution in the STRING database.
Journal ArticleDOI

The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored

TL;DR: An update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING), which provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information.
Journal ArticleDOI

An Integrated View of Molecular Coevolution in Protein–Protein Interactions

TL;DR: It is argued that both site-specific coevolutionary change and whole-sequence evolution contribute to evolutionary signals in sets of interacting proteins, permitting an integrated view of protein-protein interactions, their evolution, and coev evolution.
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Three-dimensional modeling of protein interactions and complexes is going 'omics.

TL;DR: This manuscript critically review some of the most recent developments in the field of structural bioinformatics applied to the modeling of protein interactions and complexes, from large macromolecular machines to domain-domain and peptide-mediated interactions.
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Mitochondrial-nuclear co-evolution and its effects on OXPHOS activity and regulation

TL;DR: It is argued that co evolution exists at the population and inter-specific levels and affect disease susceptibility and the existence of three modes of co-evolution in the mitochondrial genetic system, which include the interaction of mtDNA and nuclear DNA encoded proteins, nuclear protein - mtDNA-encoded RNA interaction within the mitochondrial translation machinery and nuclearDNA encoded proteins-mtDNA binging sites interaction in the frame of the mtDNA replication and transcription machineries.
References
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Journal ArticleDOI

Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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The Structure and Function of Complex Networks

Mark Newman
- 01 Jan 2003 - 
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Journal ArticleDOI

An introduction to ROC analysis

TL;DR: The purpose of this article is to serve as an introduction to ROC graphs and as a guide for using them in research.
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