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相关论文: Spectral Analysis of Protein-Protein Interactions …

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Network theorists have developed methods to characterize the complex interactions in natural phenomena. The structure of the network of interactions between proteins is important in the field of proteomics, and has been subject to intensive…

分子网络 · 定量生物学 2016-09-07 Allan A. Zea , Antonio Rueda-Toicen

Naturally occurring networks exhibit quantitative features revealing underlying growth mechanisms. Numerous network mechanisms have recently been proposed to reproduce specific properties such as degree distributions or clustering…

定量方法 · 定量生物学 2009-11-10 Manuel Middendorf , Etay Ziv , Chris Wiggins

Thanks to recent progress in high-throughput experimental techniques, the datasets of large-scale protein interactions of prototypical multicellular species, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila…

分子网络 · 定量生物学 2009-11-11 K. -I. Goh , B. Kahng , D. Kim

We employed the random graph theory approach to analyze the protein-protein interaction database DIP (Feb. 2004), for seven species (S. cerevisiae, H. pylori, E. coli, C. elegans, H. sapiens, M. musculus and D. melanogaster). Several global…

分子网络 · 定量生物学 2007-05-23 Ka-Lok Ng , Chien-Hung Huang

Protein interaction networks (PIN) are popular means to visualize the proteome. However, PIN datasets are known to be noisy, incomplete and biased by the experimental protocols used to detect protein interactions. This paper aims at…

无序系统与神经网络 · 物理学 2015-01-06 Alessia Annibale , Anthony C. C. Coolen , Nuria Planell-Morell

Cellular function is widely believed to be organized in a modular fashion. On all scales and at all levels of complexity, relatively independent sub-units perform relatively independent sub-tasks of biological function. This functional…

分子网络 · 定量生物学 2010-12-22 Stefan Pinkert , Joerg Schultz , Joerg Reichardt

Understanding of how protein interaction networks (PIN) of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce a hybrid network model composed…

分子网络 · 定量生物学 2007-05-23 K. -I. Goh , B. Kahng , D. Kim

We propose a biologically motivated quantity, twinness, to evaluate local similarity between nodes in a network. The twinness of a pair of nodes is the number of connected, labeled subgraphs of size n in which the two nodes possess…

分子网络 · 定量生物学 2009-11-13 Orion Penner , Vishal Sood , Gabe Musso , Kim Baskerville , Peter Grassberger , Maya Paczuski

The enormous diversity of life forms thriving in drastically different environmental milieus involves a complex interplay among constituent proteins interacting with each other. However, the organizational principles characterizing the…

分子网络 · 定量生物学 2024-01-30 Vikram Singh , Vikram Singh

Topological analysis of large scale protein-protein interaction networks (PINs) is important for understanding the organisational and functional principles of individual proteins. The number of interactions that a protein has in a PIN has…

分子网络 · 定量生物学 2013-04-02 Ernesto Estrada

We analyze protein-protein interaction networks for six different species under the framework of random matrix theory. Nearest neighbor spacing distribution of the eigenvalues of adjacency matrices of the largest connected part of these…

分子网络 · 定量生物学 2014-05-20 Ankit Agrawal , Camellia Sarkar , Sanjiv K. Dwivedi , Nitesh Dhasmana , Sarika Jalan

The identification of essential proteins in protein-protein interaction networks (PINs) can help to discover drug targets and prevent disease. In order to improve the accuracy of the identification of essential proteins, researchers…

分子网络 · 定量生物学 2023-12-08 Haoyue Wang , Li Pan , Bo Yang , Junqiang Jiang , Wenbin Li

Protein interaction networks (PINs) are often used to "learn" new biological function from their topology. Since current PINs are noisy, their computational de-noising via link prediction (LP) could improve the learning accuracy. LP uses…

分子网络 · 定量生物学 2013-07-15 Ryan W. Solava , Tijana Milenković

Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of 'linked selection' on levels of genetic diversity is key to making reliable inference about demography, building a null model in…

Gene regulatory networks are comprised of biochemical reactions, which are inherently stochastic. Each reaction channel contributes to this stochasticity in different measure. In this paper we study the stochastic dynamics of protein…

分子网络 · 定量生物学 2021-06-16 Jaroslav Albert

During organogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of living organisms. Robustness, thus, is an essential characteristic that GRNs…

组织与器官 · 定量生物学 2015-01-07 Daniel Aguilar-Hidalgo , M. Carmen Lemos , Antonio Córdoba

Since proteins carry out biological processes by interacting with other proteins, analyzing the structure of protein-protein interaction (PPI) networks could explain complex biological mechanisms, evolution, and disease. Similarly, studying…

分子网络 · 定量生物学 2010-04-22 Vesna Memisevic , Tijana Milenkovic , Natasa Przulj

The properties of certain networks are determined by hidden variables that are not explicitly measured. The conditional probability (propagator) that a vertex with a given value of the hidden variable is connected to k of other vertices…

定量方法 · 定量生物学 2009-11-13 Gerald A. Miller , Yi Y. Shi , Hong Qian , Karol Bomsztyk

Two processes can influence the evolution of protein interaction networks: addition and elimination of interactions between proteins, and gene duplications increasing the number of proteins and interactions. The rates of these processes can…

统计力学 · 物理学 2007-05-23 A. Wagner

Numerous cellular functions rely on protein$\unicode{x2013}$protein interactions. Efforts to comprehensively characterize them remain challenged however by the diversity of molecular recognition mechanisms employed within the proteome. Deep…

生物大分子 · 定量生物学 2023-12-08 Julia R. Rogers , Gergő Nikolényi , Mohammed AlQuraishi
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