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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Posted Content
Recovery and Analysis of Architecture Descriptions using Centrality Measures.
TL;DR: In this article, an approach to extract architecture descriptions using the {\em centrality measures} from the theory of Social Network Analysis is presented, which works in two phases and assumes that the system has been designed around the layered architecture style and assigns layers to each program element.
Journal ArticleDOI
Catalytic and binding sites prediction in globular proteins through discrete Markov chains and network centrality measures.
TL;DR: In this article, a Discrete Markov Chain (DMC) approach combined with network centrality measures was used to identify and predict the location of active sites in globular proteins.
Book ChapterDOI
Network-based strategies for protein characterization.
TL;DR: In this article, the spectral properties of the networks reconstructed from the Protein Contact Map (PCM) can be used to generate informative observables, such as protein resistance to thermal stress, up to unveiling organism pathologies.
Proceedings ArticleDOI
Functional site prediction by exploiting correlations between labels of interacting residues
TL;DR: This paper proposes a method for prediction of functional residues in a given protein from its three-dimensional (3D) structure that significantly outperforms state of the art methods on standard benchmark dataset.
Posted ContentDOI
Regional Variant Analysis of Spike Glycoprotein Mutations of SARS-CoV-2 and Its Implications in COVID-19 Pandemic Control
TL;DR: In this article, the authors analyzed all the mutations in the spike glycoprotein from123 strains isolated from Kerala, India, and predicted the possible structural relevance of the unique mutations based on topological analysis of the residue interaction network of the spike protein structure.
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.
Journal ArticleDOI
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.
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.
Journal ArticleDOI
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.
Journal ArticleDOI
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.