Journal ArticleDOI
Network analysis of protein structures identifies functional residues.
Gil Amitai,Arye Shemesh,Einat Sitbon,Maxim Shklar,Dvir Netanely,Ilya Venger,Shmuel Pietrokovski +6 more
TLDR
This work transformed protein structures into residue interaction graphs (RIGs), where amino acid residues are graph nodes and their interactions with each other are the graph edges, and found that active site, ligand-binding and evolutionary conserved residues, typically have high closeness values.About:
This article is published in Journal of Molecular Biology.The article was published on 2004-12-03. It has received 463 citations till now. The article focuses on the topics: Protein structure & Active site.read more
Citations
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The Appearance and Promotion of Creativity by Various Levels of Interdependent Networks
TL;DR: The Hungarian research student movement, its international network, the Network of Youth Excellence, the Hungarian talent support network (helping more than 25,000 talented people in the last two years) and the currently developing EU Talent Support Network will be introduced as mentioned in this paper.
Journal ArticleDOI
Opinion Prediction of protein Post-Translational Modification sites: An overview
TL;DR: Although the characterization of PTMs gets invaluable insight into the cellular functions in etiological processes, there are still challenges.
Journal ArticleDOI
Accurate prediction of protein catalytic residues by side chain orientation and residue contact density.
Yu-Tung Chien,Shao-Wei Huang +1 more
TL;DR: A novel structure feature, residue side chain orientation, is found, which is the first structure-based feature that achieves prediction results comparable to that of evolutionary sequence conservation and designed the EXIA method based on the newly discovered feature.
Journal ArticleDOI
Prediction of Protein Folding Rates from Structural Topology and Complex Network Properties
Jiangning Song,Jiangning Song,Kazuhiro Takemoto,Hong-Bin Shen,Hao Tan,M. Michael Gromiha,Tatsuya Akutsu +6 more
TL;DR: In this article, the authors developed a novel approach to predict protein folding rates for two-state and multi-state protein folding kinetics, which combines a variety of structural topology and complex network properties that are calculated from protein 3D structures.
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GraphAlignment: Bayesian pairwise alignment of biological networks
Michal Kolář,Michal Kolář,Jörn Meier,Ville Mustonen,Ville Mustonen,Michael Lässig,Johannes Berg +6 more
TL;DR: The GraphAlignment algorithm is robust to spurious vertex associations, correctly resolves paralogs, and shows very good performance in identification of homologous vertices defined by high vertex and/or interaction similarity.
References
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Journal ArticleDOI
Collective dynamics of small-world networks
TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
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The Protein Data Bank
Helen M. Berman,John D. Westbrook,Zukang Feng,Gary L. Gilliland,Talapady N. Bhat,Helge Weissig,Ilya N. Shindyalov,Philip E. Bourne +7 more
TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
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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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Statistical mechanics of complex networks
TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
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Centrality in social networks conceptual clarification
TL;DR: In this article, three distinct intuitive notions of centrality are uncovered and existing measures are refined to embody these conceptions, and the implications of these measures for the experimental study of small groups are examined.