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相关论文: The evolutionary dynamics of protein-protein inter…

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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…

分子网络 · 定量生物学 2015-01-07 Jack Peterson , Steve Presse , Kristin S. Peterson , Ken A. Dill

Genome-wide protein-protein interaction (PPI) data are readily available thanks to recent breakthroughs in biotechnology. However, PPI networks of extant organisms are only snapshots of the network evolution. How to infer the whole…

种群与进化 · 定量生物学 2012-03-13 Si Li , Kwok Pui Choi , Taoyang Wu , Louxin Zhang

Genomic duplication-divergence events, which are the primary source of new protein functions, occur stochastically at a wide range of genomic scales, from single gene to whole genome duplications. Clearly, this fundamental evolutionary…

分子网络 · 定量生物学 2007-05-23 Kirill Evlampiev , Herve Isambert

Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. It is not clear, however, how such dramatic evolutionary process has contributed to shape the large scale topology of…

分子网络 · 定量生物学 2007-05-23 K. Evlampiev , H. Isambert

The protein-protein interaction (PPI) network provides an overview of the complex biological reactions vital to an organism's metabolism and survival. Even though in the past PPI network were compared across organisms in detail, there has…

计算机视觉与模式识别 · 计算机科学 2023-10-27 Long-Huei Chen , Mohana Prasad Sathya Moorthy , Pratyaksh Sharma

Protein-protein interaction (PPI) networks are the backbone of all processes in living cells. In this work we relate conservation, essentiality and functional repertoire of a gene to the connectivity $k$ (i.e., the number of interaction…

基因组学 · 定量生物学 2021-02-23 Maddalena Dilucca , Giulio Cimini , Andrea Giansanti

Complexes of physically interacting proteins are one of the fundamental functional units responsible for driving key biological mechanisms within the cell. Their identification is therefore necessary not only to understand complex formation…

计算工程、金融与科学 · 计算机科学 2012-11-27 Sriganesh Srihari , Hon Wai Leong

We introduce a graph generating model aimed at representing the evolution of protein interaction networks. The model is based on the hypotesis of evolution by duplications and divergence of the genes which produce proteins. The obtained…

统计力学 · 物理学 2007-05-23 A. Vazquez , A. Flammini , A. Maritan , A. Vespignani

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

Protein-protein interactions (PPIs) are crucial in regulating numerous cellular functions, including signal transduction, transportation, and immune defense. As the accuracy of multi-chain protein complex structure prediction improves, the…

生物大分子 · 定量生物学 2024-02-07 Chenqing Hua , Connor Coley , Guy Wolf , Doina Precup , Shuangjia Zheng

The structure of molecular networks derives from dynamical processes on evolutionary time scales. For protein interaction networks, global statistical features of their structure can now be inferred consistently from several…

统计力学 · 物理学 2007-05-23 Johannes Berg , Michael Lässig , Andreas Wagner

Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand…

分子网络 · 定量生物学 2015-05-21 Sriganesh Srihari , Chern Han Yong , Ashwini Patil , Limsoon Wong

Protein-protein interaction (PPI) networks, providing a comprehensive landscape of protein interacting patterns, enable us to explore biological processes and cellular components at multiple resolutions. For a biological process, a number…

分子网络 · 定量生物学 2016-04-13 Xiuli Ma , Guangyu Zhou , Jingjing Wang , Jian Peng , Jiawei Han

Background:Typically, proteins perform key biological functions by interacting with each other. As a consequence, predicting which protein pairs interact is a fundamental problem. Experimental methods are slow, expensive, and may be error…

生物大分子 · 定量生物学 2022-02-08 Leonardo Martini , Adriano Fazzone , Luca Becchetti

The function of a protein is defined by its interaction partners. Thus, topology-driven network alignment of the protein-protein interaction (PPI) networks of two species should uncover similar interaction patterns and allow identification…

Background. Human aging is linked to many prevalent diseases. The aging process is highly influenced by genetic factors. Hence, it is important to identify human aging-related genes. We focus on supervised prediction of such genes. Gene…

分子网络 · 定量生物学 2020-04-28 Qi Li , Tijana Milenković

Aligning protein-protein interaction (PPI) networks of different species has drawn a considerable interest recently. This problem is important to investigate evolutionary conserved pathways or protein complexes across species, and to help…

最优化与控制 · 数学 2009-05-08 Mikhail Zaslavskiy , Francis Bach , Jean-Philippe Vert

Biological networks provide insight into the complex organization of biological processes in a cell at the system level. They are an effective tool for understanding the comprehensive map of functional interactions, finding the functional…

分子网络 · 定量生物学 2017-09-14 Somaye Hashemifar

Living systems rely on coordinated molecular interactions, especially those related to gene expression and protein activity. The Unfolded Protein Response is a crucial mechanism in eukaryotic cells, activated when unfolded proteins exceed a…

We show that the protein-protein interaction networks can be surprisingly well described by a very simple evolution model of duplication and divergence. The model exhibits a remarkably rich behavior depending on a single parameter, the…

分子网络 · 定量生物学 2009-11-10 I. Ispolatov , P. L. Krapivsky , A. Yuryev
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