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Related papers: Modeling Protein Contact Networks

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As proteins with similar structures often have similar functions, analysis of protein structures can help predict protein functions and is thus important. We consider the problem of protein structure classification, which computationally…

Machine Learning · Statistics 2019-10-08 Hongyu Guo , Khalique Newaz , Scott Emrich , Tijana Milenkovic , Jun Li

Several processes in the cell, such as gene regulation, start when key proteins recognise and bind to short DNA sequences. However, as these sequences can be hundreds of million times shorter than the genome, they are hard to find by simple…

Subcellular Processes · Quantitative Biology 2021-01-27 Markus Nyberg , Tobias Ambjörnsson , Per Stenberg , and Ludvig Lizana

Data describing the three-dimensional structure of physical networks is increasingly available, leading to a surge of interest in network science to explore the relationship between the shape and connectivity of physical networks. We…

Physics and Society · Physics 2024-08-20 Luka Blagojević , Márton Pósfai

Although both RNA and proteins have densely packed native structures, chain organizations of these two biopolymers are fundamentally different. Motivated by the recent discoveries in chromatin folding that interphase chromosomes have…

Soft Condensed Matter · Physics 2016-12-28 Lei Liu , Changbong Hyeon

Proteins are the workhorse molecules of the cell and perform their biological functions by binding to other molecules through physical contact. Protein function is then regulated through coupling of bindings on the protein (allosteric…

Biomolecules · Quantitative Biology 2025-09-24 Naoto Morikawa

Community structure is one of the key properties of complex networks and plays a crucial role in their topology and function. While an impressive amount of work has been done on the issue of community detection, very little attention has…

Physics and Society · Physics 2010-09-17 Andrea Lancichinetti , Mikko Kivela , Jari Saramaki , Santo Fortunato

We constructs a new network by superposition of hexahedron , which are scale-free, highly sparse,disassortative ,and maximal planar graphs. The network degree distribution, agglomeration coefficient and degree of correlation are computed…

Physics and Society · Physics 2021-04-12 Li Haijun , Lu Qingping

Meso-scale structures are network features where nodes with similar properties are grouped together instead of being treated individually. In this work, we provide formal and mathematical definitions of three such structures: assortative…

Social and Information Networks · Computer Science 2022-04-01 Eric Yanchenko

Proteins are fundamental biological entities that play a key role in life activities. The amino acid sequences of proteins can be folded into stable 3D structures in the real physicochemical world, forming a special kind of…

Machine Learning · Computer Science 2023-01-04 Lirong Wu , Yufei Huang , Haitao Lin , Stan Z. Li

Long, flexible physical filaments are naturally tangled and knotted, from macroscopic string down to long-chain molecules. The existence of knotting in a filament naturally affects its configuration and properties, and may be very stable or…

Biomolecules · Quantitative Biology 2016-11-21 Keith Alexander , Alexander J Taylor , Mark R Dennis

Proteins are the fundamental macromolecules that play diverse and crucial roles in all living matter and have tremendous implications in healthcare, manufacturing, and biotechnology. Their functions are largely determined by the sequences…

Biomolecules · Quantitative Biology 2024-09-17 Boqiao Lai

The biological function of a protein stems from its 3-dimensional structure, which is thermodynamically determined by the energetics of interatomic forces between its amino acid building blocks (the order of amino acids, known as the…

Biomolecules · Quantitative Biology 2019-05-03 Sean Mullane , Ruoyan Chen , Sri Vaishnavi Vemulapalli , Eli J. Draizen , Ke Wang , Cameron Mura , Philip E. Bourne

Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and other biological macromolecules. Topological coarse-graining, in which biomolecules or sets thereof are represented via graph structures, is a…

Biomolecules · Quantitative Biology 2021-09-15 Vy Duong , Elizabeth Diessner , Gianmarc Grazioli , Rachel W. Martin , Carter T. Butts

The Saccharomyces cerevisiae protein-protein interaction map, as well as many natural and man-made networks, shares the scale-free topology. The preferential attachment model was suggested as a generic network evolution model that yields…

Statistical Mechanics · Physics 2007-05-23 Eli Eisenberg , Erez Y. Levanon

Complex networks has been a hot topic of research over the past several years over crossing many disciplines, starting from mathematics and computer science and ending by the social and biological sciences. Random graphs were studied to…

Computers and Society · Computer Science 2021-01-28 Alaa Eddin Alchalabi

It has recently been demonstrated that many biological networks exhibit a scale-free topology where the probability of observing a node with a certain number of edges (k) follows a power law: i.e. p(k) ~ k^-g. This observation has been…

Molecular Networks · Quantitative Biology 2009-11-11 Eric J. Deeds , Orr Ashenberg , Eugene I. Shakhnovich

Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin…

We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate…

Molecular Networks · Quantitative Biology 2015-01-07 Jack Peterson , Steve Presse , Kristin S. Peterson , Ken A. Dill

A general scheme for detecting and analyzing topological patterns in large complex networks is presented. In this scheme the network in question is compared with its properly randomized version that preserves some of its low-level…

Statistical Mechanics · Physics 2008-03-25 Sergei Maslov , Kim Sneppen , Alexei Zaliznyak

To characterize the dynamical features of seismicity as a complex phenomenon, the seismic data is mapped to a growing random graph, which is a small-world scale-free network. Here, hierarchical and mixing properties of such a network are…

Disordered Systems and Neural Networks · Physics 2009-11-11 Sumiyoshi Abe , Norikazu Suzuki