A survey of computational methods in protein–protein interaction networks

被引:0
作者
Saeid Rasti
Chrysafis Vogiatzis
机构
[1] North Dakota State University,Department of Industrial and Manufacturing Engineering
[2] North Carolina A&T State University,Department of Industrial and Systems Engineering
来源
Annals of Operations Research | 2019年 / 276卷
关键词
Protein–protein interaction networks; Modularity; Clustering; Centrality; Protein essentiality;
D O I
暂无
中图分类号
学科分类号
摘要
Protein–protein interaction networks are mathematical constructs where every protein is represented as a node, with an edge signaling that two proteins interact. These constructs have enabled a series of graph theoretic computational methods in the analysis of how cell life works. Such methods have found diverse applications from helping create more reliable interaction data, to identifying new protein complexes and predict their functionalities, and investigating the minimum requirements for cell life through protein essentiality. Our goal with this survey is to provide an overview of the research in the area from a network analysis perspective. In this work, we provide a brief introduction to protein–protein interaction networks, followed by the methods that we currently have to obtain such interactions and the databases they can be found at. Then, we proceed to discuss the network properties of protein–protein interaction networks and how they can be exploited to identify protein complexes and functional modules, as well as help classify proteins as essential. We finish this survey with a full bibliography on work in protein–protein interactions that could be of interest to operations research and computational science academicians and practitioners.
引用
收藏
页码:35 / 87
页数:52
相关论文
共 1444 条
[1]  
Acencio ML(2009)Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information BMC Bioinformatics 10 290-1023
[2]  
Lemke N(2006)Cfinder: Locating cliques and overlapping modules in biological networks Bioinformatics 22 1021-255
[3]  
Adamcsek B(2006)Graph-based methods for analysing networks in cell biology Briefings in Bioinformatics 7 243-238
[4]  
Palla G(2011)Integrating protein–protein interaction networks with gene–gene co-expression networks improves gene signatures for classifying breast cancer metastasis Journal of Integrative Bioinformatics (JIB) 8 222-W535
[5]  
Farkas IJ(2016)APID interactomes: Providing proteome-based interactomes with controlled quality for multiple species and derived networks Nucleic Acids Research 44 W529-162
[6]  
Derényi I(2003)Interprets: Protein interaction prediction through tertiary structure Bioinformatics 19 161-W327
[7]  
Vicsek T(2006)Development and implementation of an algorithm for detection of protein complexes in large interaction networks BMC Bioinformatics 7 207-2749
[8]  
Aittokallio T(2011)Bioprofiling. De: Analytical web portal for high-throughput cell biology Nucleic Acids Research 39 W323-378
[9]  
Schwikowski B(2009)PPI spider: A tool for the interpretation of proteomics data in the context of protein–protein interaction networks Proteomics 9 2740-i40
[10]  
Akker EVD(2004)Iterative cluster analysis of protein interaction data Bioinformatics 21 364-2855