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      NetMatchStar: an enhanced Cytoscape network querying app

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          Abstract

          We present NetMatchStar, a Cytoscape app to find all the occurrences of a query graph in a network and check for its significance as a motif with respect to seven different random models. The query can be uploaded or built from scratch using Cytoscape facilities. The app significantly enhances the previous NetMatch in style, performance and functionality. Notably NetMatchStar allows queries with wildcards.

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          Most cited references 32

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          Emergence of scaling in random networks

          Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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            Statistical mechanics of complex networks

            Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks.
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              CFinder: Locating cliques and overlapping modules in biological networks

              Summary: Most cellular tasks are performed not by individual proteins, but by groups of functionally associated proteins, often referred to as modules. In a protein assocation network modules appear as groups of densely interconnected nodes, also called communities or clusters. These modules often overlap with each other and form a network of their own, in which nodes (links) represent the modules (overlaps). We introduce CFinder, a fast program locating and visualizing overlapping, densely interconnected groups of nodes in undirected graphs, and allowing the user to easily navigate between the original graph and the web of these groups. We show that in gene (protein) association networks CFinder can be used to predict the function(s) of a single protein and to discover novel modules. CFinder is also very efficient for locating the cliques of large sparse graphs. Availability: CFinder (for Windows, Linux, and Macintosh) and its manual can be downloaded from http://angel.elte.hu/clustering. Contact: cfinder@angel.elte.hu
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                Author and article information

                Journal
                F1000Res
                F1000Res
                F1000Research
                F1000Research
                F1000Research (London, UK )
                2046-1402
                5 August 2015
                2015
                : 4
                Affiliations
                [1 ]Department of Maths and Computer Science, University of Catania, Catania, 95125, Italy
                [2 ]Department of Computer Science, University of Verona, Verona, 37134, Italy
                [3 ]The Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
                [4 ]Department of Computer Science,, Courant Institute of Mathematical Sciences, New York University, New York, NY, 10012, USA
                [5 ]Department of Clinical and Experimental Medicine, University of Catania, Catania, 95125, Italy
                [1 ]Vishuo BioMedical Pte Ltd, Singapore, Singapore
                [1 ]Computer Science Department, University of California, Santa Barbara, Santa Barbara, CA, USA
                Author notes

                RG conceived the project. FR, GM and VB enabled the porting of the code to the new versions of Cytoscape (from version 3.0 onward) and extended the functionality of the application. In particular, GM has worked on the statistical significance and VB on the graph matching algorithm. RG, GM, and AP wrote the main parts of the paper. All authors have tested, validated, improved the software and the manuscript.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Article
                10.12688/f1000research.6656.1
                4642848
                Copyright: © 2015 Rinnone F et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Product
                Funding
                Funded by: ProgrammaOperativoFondoEuropeo per lo SviluppoRegionale
                Award ID: PO-FESR 2007-2013
                Funded by: Linea di intervento 4.1.1.2.
                Award ID: CUP G23F11000840004
                RG, AP and AF have been founded by ProgrammaOperativoFondoEuropeo per lo SviluppoRegionale (PO-FESR 2007-2013), Linea di intervento 4.1.1.2. Grant number: CUP G23F11000840004.
                Categories
                Software Tool Article
                Articles
                Bioinformatics
                Theory & Simulation

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