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      EviNet: a web platform for network enrichment analysis with flexible definition of gene sets

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          Abstract

          The new web resource EviNet provides an easily run interface to network enrichment analysis for exploration of novel, experimentally defined gene sets. The major advantages of this analysis are (i) applicability to any genes found in the global network rather than only to those with pathway/ontology term annotations, (ii) ability to connect genes via different molecular mechanisms rather than within one high-throughput platform, and (iii) statistical power sufficient to detect enrichment of very small sets, down to individual genes. The users’ gene sets are either defined prior to upload or derived interactively from an uploaded file by differential expression criteria. The pathways and networks used in the analysis can be chosen from the collection menu. The calculation is typically done within seconds or minutes and the stable URL is provided immediately. The results are presented in both visual (network graphs) and tabular formats using jQuery libraries. Uploaded data and analysis results are kept in separated project directories not accessible by other users. EviNet is available at https://www.evinet.org/.

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          Most cited references40

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

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            Gene Ontology: tool for the unification of biology

            Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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              PhosphoSitePlus: a comprehensive resource for investigating the structure and function of experimentally determined post-translational modifications in man and mouse

              PhosphoSitePlus (http://www.phosphosite.org) is an open, comprehensive, manually curated and interactive resource for studying experimentally observed post-translational modifications, primarily of human and mouse proteins. It encompasses 1 30 000 non-redundant modification sites, primarily phosphorylation, ubiquitinylation and acetylation. The interface is designed for clarity and ease of navigation. From the home page, users can launch simple or complex searches and browse high-throughput data sets by disease, tissue or cell line. Searches can be restricted by specific treatments, protein types, domains, cellular components, disease, cell types, cell lines, tissue and sequences or motifs. A few clicks of the mouse will take users to substrate pages or protein pages with sites, sequences, domain diagrams and molecular visualization of side-chains known to be modified; to site pages with information about how the modified site relates to the functions of specific proteins and cellular processes and to curated information pages summarizing the details from one record. PyMOL and Chimera scripts that colorize reactive groups on residues that are modified can be downloaded. Features designed to facilitate proteomic analyses include downloads of modification sites, kinase–substrate data sets, sequence logo generators, a Cytoscape plugin and BioPAX download to enable pathway visualization of the kinase–substrate interactions in PhosphoSitePlus®.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                02 July 2018
                09 June 2018
                09 June 2018
                : 46
                : Web Server issue
                : W163-W170
                Affiliations
                [1 ]Department of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden
                [2 ]Department of Microbiology, Tumor and Cell Biology (MTC), Karolinska Institutet, Stockholm, Sweden
                [3 ]National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Box 1031, 171 21 Solna, Sweden
                Author notes
                To whom correspondence should be addressed. Tel: +46 8 52481513; Email: andrej.alekseenko@ 123456scilifelab.se
                Author information
                http://orcid.org/0000-0001-8812-6481
                Article
                gky485
                10.1093/nar/gky485
                6030852
                29893885
                e5460cc2-b2c6-4a87-8d37-9185137d23ad
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 29 May 2018
                : 05 May 2018
                : 25 February 2018
                Page count
                Pages: 8
                Funding
                Funded by: Swedish Foundation for Strategic research 10.13039/501100001729
                Award ID: SRL10-0030
                Funded by: Knut and Alice Wallenberg Foundation 10.13039/501100004063
                Award ID: KAW2011.0161
                Award ID: KAW2012.0101
                Funded by: Swedish Research Council 10.13039/501100004359
                Award ID: D0415501
                Award ID: 2016-04940
                Funded by: Cancerfonden 10.13039/501100002794
                Award ID: 110578
                Categories
                Web Server Issue

                Genetics
                Genetics

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