Superclusteroid 2.0: A Web Tool for Processing Big Biological Networks
Biological networks have been the most prevalent model to analyze the complexity of cellular mechanisms. The expansion of the existing knowledge on known intracellular players such as genes, RNA molecules and proteins as long as the continued study on the
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epartment of Computer Engineering and Informatics, University of Patras, Patras, Greece {thom,tsitsoue,panges,mosxopul,alexopo,giannul, likothan}@ceid.upatras.gr 2 InSyBio Ltd., 109 Uxbridge Road, London, UK {k.theofilatos,c.alexakos}@insybio.com 3 Department of Social Work, Technological Institute of Western Greece, Patras, Greece [email protected]
Abstract. Biological networks have been the most prevalent model to analyze the complexity of cellular mechanisms. The expansion of the existing knowledge on known intracellular players such as genes, RNA molecules and proteins as long as the continued study on their interactions has increased lately the ability to construct big biological networks of increased complexity. Many web tools have been introduced in the last decade but they are incomplete, as they do not provide all required features for a full research study neither they can handle the big and complex nature of these networks and the increased needs of researchers for fast and uninterrupted analysis. In the present paper, the new version of the Superclusteroid tool is presented which includes among others new visualization features, network comparison tools and new clustering algorithms. Moreover, a new strategy is proposed to deal with the necessity of handling effectively the increased work load of the tool as long as to improve the speed in the two most time consuming steps: network visualization and network clustering. Keywords: Web tool · Biological networks · Protein-protein interaction networks · Network clustering · Network visualization
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Introduction
Network visualization is a fundamental method that helps scientists in understanding biological networks and important properties in underlying biochemical processes. Molecules such as DNA, RNA, proteins, metabolites and interactions between them are related to highly important biological networks. Whenever such molecules are connected by physical interactions, they form molecular interaction networks that are generally classified by the nature of the compounds involved. Many biological networks have been characterized in detail: Protein-Protein Interaction (PPI), Gene co-expression © IFIP International Federation for Information Processing 2016 Published by Springer International Publishing Switzerland 2016. All Rights Reserved L. Iliadis and I. Maglogiannis (Eds.): AIAI 2016, IFIP AICT 475, pp. 623–633, 2016. DOI: 10.1007/978-3-319-44944-9_55
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networks (Transcript-Transcript association networks), Gene regulatory networks (DNA-protein interaction networks), protein phosphorylation, metabolic interactions, and genetic interaction networks [1]. The PPIs represent the interaction between proteins: e.g. the formulation of protein complexes and the activation of one protein by another protein. These interactions are essential to almost every process in a cell, thus understanding of them is crucial. Such a network can be defined as an un-directed graph G = (V, E) .where V is the set of proteins represented as nodes and
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