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      A systems biology analysis protein-protein interaction of NASH and IBD based on comprehensive gene information

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          Abstract

          Aim:

          Analysis reconstruction networks from two diseases, IBD and NASH and their relationship, based on systems biology methods.

          Background:

          IBD and NASH are two complex diseases, with progressive prevalence and high cost for countries. There are some reports on co-existence of these two diseases. In addition, they have some similar risk factors such as age, obesity, and insulin resistance. Therefore, systems biology approach can help to discover their relationship.

          Methods:

          DisGeNET and STRING databases were sources of disease genes and constructing networks. Three plugins of Cytoscape software, including ClusterONE, ClueGO and CluePedia, were used to analyze and cluster networks and enrichment of pathways. Based on degree and Betweenness, hubs and bottleneck nodes were defined.

          Results:

          Common genes between IBD and NASH construct a network with 99 nodes. Common genes between IBD and NASH were extracted and imported to STRING database to construct PPI network. The resulting network contained 99 nodes and 333 edges. Five genes were selected as hubs: JAK2, TLR2, TP53, TLR4 and STAT3 and five genes were selected as bottleneck including: JAK2, TP53, AGT, CYP3A4 and TLR4. These genes were hubs in analysis network that was constructed from hubs of NASH and IBD networks.

          Conclusion:

          Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases. Finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.

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          Most cited references55

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

            Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: jerome.galon@crc.jussieu.fr Supplementary information: Supplementary data are available at Bioinformatics online.
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              DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

              The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
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                Author and article information

                Journal
                Gastroenterol Hepatol Bed Bench
                Gastroenterol Hepatol Bed Bench
                GHFBB
                Gastroenterology and Hepatology From Bed to Bench
                Shaheed Beheshti University of Medical Sciences (Tehran, Iran )
                2008-2258
                2008-4234
                Summer 2017
                : 10
                : 3
                : 194-201
                Affiliations
                [1 ] Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
                [2 ] Drug Design and Bioinformatics Unit, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
                [3 ] Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases Shahid Beheshti University Medical Sciences, Tehran, Iran
                Author notes
                Reprint or Correspondence: Mohammad Hossein Heidari, PhD. Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. E-mail: mhheidari@sbmu.ac.ir
                Article
                GHFBB-10-194
                5660269
                29118935
                a28d7609-80a6-4b52-8d21-1fa76fb2888a
                ©2017 RIGLD, Research Institute for Gastroenterology and Liver Diseases

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License, ( http://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 June 2017
                : 27 September 2017
                Categories
                Original Article

                inflammatory bowel diseases (ibd),non-alcoholic steatohepatitis (nash),protein-protein interaction (ppi) network analysis,hub-bottlenecks,protein clusters

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