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      BioNetApp: An interactive visual data analysis platform for molecular expressions

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          Abstract

          Motivation

          Systems biology faces two key challenges when dealing with large amounts of disparate data produced by different experiments: the integration of results across different experiments, and the extraction of meaningful information from the data produced by these experiments. An ongoing challenge is to provide better tools that can mine data patterns that could not have been discovered through simple visualization. Such mining capabilities also need to be coupled with intuitive visualization to portray those findings. We introduce a software toolbox entitled BioNetApp to mine these patterns and visualize them across all experiments.

          Results

          BioNetApp is an interactive visual data mining software for analyzing high-volume molecular expression data obtained from multiple ‘omics experiments. By integrating visualization, statistical methods, and data mining techniques, BioNetApp can perform interactive correlative and comparative analysis along time-course studies of molecular expression data. Correlation analysis provides several visualization features such as Kamada-Kawai, Fruchterman-Reingold Spring embedding network layouts, in addition to single circle, multiple circle and heatmap layouts, whereas comparative analysis presents expression-data distributions across samples, groups, and time points with boxplot display, outlier detection, and data curve fitting. BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.

          Conclusion

          BioNetApp has been utilized in a metabolomics study to investigate the metabolite abundance changes in alcohol induced fatty liver, where pair-wise analyses of metabolome concentration revealed correlation networks and interesting patterns in the metabolomics dataset. This study case demonstrates the effectiveness of the BioNetApp software as an interactive visual analysis tool for molecular expression data in systems biology. The BioNetApp software is freely available under GNU GPL license and can be downloaded (including the case-study data and user-manual) at: https://doi.org/10.5281/zenodo.2563129.

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          Most cited references13

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          A New Measure of Rank Correlation

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            CFinder: locating cliques and overlapping modules in biological networks

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              Chronic Alcohol Exposure Disturbs Lipid Homeostasis at the Adipose Tissue-Liver Axis in Mice: Analysis of Triacylglycerols Using High-Resolution Mass Spectrometry in Combination with In Vivo Metabolite Deuterium Labeling

              A method of employing high-resolution mass spectrometry in combination with in vivo metabolite deuterium labeling was developed in this study to investigate the effects of alcohol exposure on lipid homeostasis at the white adipose tissue (WAT)-liver axis in a mouse model of alcoholic fatty liver. In order to differentiate the liver lipids synthesized from the fatty acids that were transported back from adipose tissue and the lipids synthesized from other sources of fatty acids, a two-stage mouse feeding experiment was performed to incorporate deuterium into metabolites. Hepatic lipids extracted from mouse liver, epididymal white adipose tissue (eWAT) and subcutaneous white adipose tissue (sWAT) were analyzed. It was found that 13 and 10 triacylglycerols (TGs) incorporated with a certain number of deuterium were significantly increased in alcohol induced fatty liver at two and four weeks of alcohol feeding periods, respectively. The concentration changes of these TGs ranged from 1.7 to 6.3-fold increase. A total of 14 deuterated TGs were significantly decreased in both eWAT and sWAT at the two and four weeks and the fold-change ranged from 0.19 to 0.77. The increase of deuterium incorporated TGs in alcohol-induced fatty liver and their decrease in both eWAT and sWAT indicate that alcohol exposure induces hepatic influx of fatty acids which are released from WATs. The results of time course analysis further indicate a mechanistic link between adipose fat loss and hepatic fat gain in alcoholic fatty liver.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: MethodologyRole: SoftwareRole: ValidationRole: Visualization
                Role: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: SupervisionRole: Writing – original draft
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                22 February 2019
                2019
                : 14
                : 2
                : e0211277
                Affiliations
                [1 ] Department of Computer Science, Gulf University for Science and Technology, Mishref, Kuwait
                [2 ] Bindley Bioscience Center, Purdue University, West Lafayette, IN, United States of America
                [3 ] Department of Computer Science, Purdue University, West Lafayette, IN, United States of America
                [4 ] Qatar Computing Research Institute, Qatar Foundation, Doha, Qatar
                [5 ] Department of Chemistry, University of Louisville, Louisville, KY, United States of America
                Weizmann Institute of Science, ISRAEL
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-1840-9712
                Article
                PONE-D-18-25534
                10.1371/journal.pone.0211277
                6386483
                30794548
                06704497-6053-4f95-9be7-908781c2ee1e
                © 2019 Roumani et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 2 September 2018
                : 10 January 2019
                Page count
                Figures: 6, Tables: 1, Pages: 16
                Funding
                This work was funded by NIH 1RO1GM087735, Purdue Cyber Center, and Purdue Bindley Bioscience Center. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Computer and Information Sciences
                Information Technology
                Data Mining
                Computer and Information Sciences
                Data Visualization
                Computer and Information Sciences
                Data Visualization
                Infographics
                Graphs
                Computer and Information Sciences
                Software Engineering
                Software Tools
                Engineering and Technology
                Software Engineering
                Software Tools
                Computer and Information Sciences
                Network Analysis
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolites
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Cluster Analysis
                Biology and Life Sciences
                Computational Biology
                Biological Data Management
                Custom metadata
                The BioNetApp software is freely available under GNU GPL license and can be downloaded (including the case-study data and user-manual) at: https://doi.org/10.5281/zenodo.2563129. In addition, all relevant data are within the manuscript and its Supporting Information files.

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