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      Multiple Sclerosis Atlas: A Molecular Map of Brain Lesion Stages in Progressive Multiple Sclerosis

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          Abstract

          Introduction: Multiple sclerosis (MS) is a chronic disorder of the central nervous system with an untreatable late progressive phase. Molecular maps of different stages of brain lesion evolution in patients with progressive multiple sclerosis (PMS) are missing but critical for understanding disease development and to identify novel targets to halt progression.

          Materials and Methods: The MS Atlas database comprises comprehensive high-quality transcriptomic profiles of 98 white matter (WM) brain samples of different lesion types (normal-appearing WM [NAWM], active, chronic active, inactive, remyelinating) from ten progressive MS patients and 25 WM areas from five non-neurological diseased cases.

          Results: We introduce the first MS brain lesion atlas ( msatlas.dk), developed to address the current challenges of understanding mechanisms driving the fate on a lesion basis. The MS Atlas gives means for testing research hypotheses, validating biomarkers and drug targets. It comes with a user-friendly web interface, and it fosters bioinformatic methods for de novo network enrichment to extract mechanistic markers for specific lesion types and pathway-based lesion type comparison. We describe examples of how the MS Atlas can be used to extract systems medicine signatures and demonstrate the interface of MS Atlas.

          Conclusion: This compendium of mechanistic PMS WM lesion profiles is an invaluable resource to fuel future MS research and a new basis for treatment development.

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          Most cited references37

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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.

                Author and article information

                Journal
                Netw Syst Med
                Netw Syst Med
                nsm
                Network and Systems Medicine
                Mary Ann Liebert, Inc., publishers (140 Huguenot Street, 3rd FloorNew Rochelle, NY 10801USA )
                2690-5949
                August 2020
                2020
                27 August 2020
                : 3
                : 1
                : 122-129
                Affiliations
                [ 1 ]Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.
                [ 2 ]Neurology Research Unit, Department of Neurology, Odense University Hopsital, Odense, Denmark.
                [ 3 ]Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
                [ 4 ]Division of Brain Science, Imperial College, London, United Kingdom.
                [ 5 ]Department of Psychiatry, University of Southern Denmark, Odense, Denmark.
                [ 6 ]Research Group Computational Systems Medicine, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
                [ 7 ]Department of Clinical Genetics, Odense University Hospital, Odense, Denmark.
                [ 8 ]Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
                Author notes
                [†]

                These authors contributed equally to this study.

                This article was previously published in bioRxiv ( www.biorxiv.org): https://doi.org/10.1101/2020.06.05.136382

                [*] [ * ]Address correspondence to: Zsolt Illes, MD, PhD, DSc, Neurology Research Unit, Department of Neurology, Odense University Hopsital, 5000 Odense, Denmark, zsolt.illes@ 123456rsyd.dk
                Article
                10.1089/nsm.2020.0006
                10.1089/nsm.2020.0006
                7500075
                32954379
                4fd37180-cea2-461a-aa5e-323902c28477
                © Tobias Frisch et al., 2020; Published by Mary Ann Liebert, Inc.

                This Open Access article is distributed under the terms of the Creative Commons License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : Accepted July 13, 2020
                Page count
                Figures: 3, Tables: 2, References: 46, Pages: 8
                Categories
                Original Research

                human brain lesions,lesion-specific heatmaps and networks,ms atlas,multiple sclerosis,natalizumab,transcriptome,vla4

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