Tools for analysis of biochemical network topology

The biochemical networks can present the relationships between genes and gene products, proteins, metabolites and etc. The exploration of these networks helps to understand cellular processes, functions or properties of biological system. The growing size of interaction models of biological system building elements request determination of the most important topological measurements of given task and powerful automated software tools to perform the analysis. The network structure measures and properties are categorized in five groups: topological parameters, topological features, network metrics, network motifs and quantitative parameters of whole network structure. Topology analysis related features of software tools Cytoscape with plug-ins BiNoM and NetworkAnalyzer, VisANT, Biological Networks and CelNetAnalyser are reviewed to simplify the task-dependent choice. The applicability of software tools for calculation of 44 topological features is summarized. Research resulted in overview on biochemical network structure analysis, on used topological features with the following goals: 1) to accumulate the existing knowledge about the network structure analysis; 2) to provide a list of topological parameters and features; 3) to provide the information of the existing software tools for the structure analysis.

[1]  Hiroaki Kitano,et al.  Biological robustness , 2008, Nature Reviews Genetics.

[2]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[3]  H. Lodish Molecular Cell Biology , 1986 .

[4]  Network Degree Distributions , 2008 .

[5]  S. Strogatz Exploring complex networks , 2001, Nature.

[6]  E. Shakhnovich,et al.  Sensitivity-dependent model of protein–protein interaction networks , 2006, Physical biology.

[7]  Sharad Bhartiya,et al.  Multiple feedback loops are key to a robust dynamic performance of tryptophan regulation in Escherichia coli , 2004, FEBS letters.

[8]  P. Bork,et al.  Evolution of biomolecular networks — lessons from metabolic and protein interactions , 2009, Nature Reviews Molecular Cell Biology.

[9]  Kwang-Hyun Cho,et al.  Analysis of feedback loops and robustness in network evolution based on Boolean models , 2007, BMC Bioinformatics.

[10]  Egils Stalidzans,et al.  EVOLUTION OF ALTERNATIVE CONTROL LOOPS OF BIOLOGICAL SYSTEMS , 2012 .

[11]  Matthew Suderman,et al.  Tools for visually exploring biological networks , 2007, Bioinform..

[12]  Peipei Zhou,et al.  Coupled positive feedback loops regulate the biological behavior , 2012, 2012 IEEE 6th International Conference on Systems Biology (ISB).

[13]  Jingtai Han Understanding biological functions through molecular networks , 2008, Cell Research.

[14]  Luonan Chen,et al.  Biomolecular Networks: Methods and Applications in Systems Biology , 2009 .

[15]  Dirk Walther,et al.  The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles , 2008, BMC Syst. Biol..

[16]  M. Gerstein,et al.  Getting connected: analysis and principles of biological networks. , 2007, Genes & development.

[17]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[18]  Robin J. Wilson Introduction to Graph Theory , 1974 .

[19]  Lan V. Zhang,et al.  Evidence for dynamically organized modularity in the yeast protein–protein interaction network , 2004, Nature.

[20]  Kwang-Hyun Cho,et al.  Coupled feedback loops form dynamic motifs of cellular networks. , 2008, Biophysical journal.

[21]  Matthew A. Hibbs,et al.  Visualization of omics data for systems biology , 2010, Nature Methods.

[22]  H Kitano,et al.  The theory of biological robustness and its implication in cancer. , 2007, Ernst Schering Research Foundation workshop.

[23]  Emmanuel Barillot,et al.  BiNoM: a Cytoscape plugin for manipulating and analyzing biological networks , 2008, Bioinform..

[24]  Zhenjun Hu,et al.  VisANT: data-integrating visual framework for biological networks and modules , 2005, Nucleic Acids Res..

[25]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

[26]  Paul T. Jackway,et al.  Network Motifs, Feedback Loops and the Dynamics of Genetic Regulatory Networks , 2005, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

[27]  Fidel Ramírez,et al.  Computing topological parameters of biological networks , 2008, Bioinform..

[28]  Kwang-Hyun Cho,et al.  Coupled positive and negative feedback circuits form an essential building block of cellular signaling pathways. , 2007, BioEssays : news and reviews in molecular, cellular and developmental biology.

[29]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[30]  T. Ideker,et al.  A new approach to decoding life: systems biology. , 2001, Annual review of genomics and human genetics.