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      HPIDB 2.0: a curated database for host–pathogen interactions

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          Abstract

          Identification and analysis of host–pathogen interactions (HPI) is essential to study infectious diseases. However, HPI data are sparse in existing molecular interaction databases, especially for agricultural host–pathogen systems. Therefore, resources that annotate, predict and display the HPI that underpin infectious diseases are critical for developing novel intervention strategies. HPIDB 2.0 ( http://www.agbase.msstate.edu/hpi/main.html) is a resource for HPI data, and contains 45, 238 manually curated entries in the current release. Since the first description of the database in 2010, multiple enhancements to HPIDB data and interface services were made that are described here. Notably, HPIDB 2.0 now provides targeted biocuration of molecular interaction data. As a member of the International Molecular Exchange consortium, annotations provided by HPIDB 2.0 curators meet community standards to provide detailed contextual experimental information and facilitate data sharing. Moreover, HPIDB 2.0 provides access to rapidly available community annotations that capture minimum molecular interaction information to address immediate researcher needs for HPI network analysis. In addition to curation, HPIDB 2.0 integrates HPI from existing external sources and contains tools to infer additional HPI where annotated data are scarce. Compared to other interaction databases, our data collection approach ensures HPIDB 2.0 users access the most comprehensive HPI data from a wide range of pathogens and their hosts (594 pathogen and 70 host species, as of February 2016). Improvements also include enhanced search capacity, addition of Gene Ontology functional information, and implementation of network visualization. The changes made to HPIDB 2.0 content and interface ensure that users, especially agricultural researchers, are able to easily access and analyse high quality, comprehensive HPI data. All HPIDB 2.0 data are updated regularly, are publically available for direct download, and are disseminated to other molecular interaction resources.

          Database URL: http://www.agbase.msstate.edu/hpi/main.html

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          Most cited references29

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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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            DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions.

            I Xenarios (2002)
            The Database of Interacting Proteins (DIP: http://dip.doe-mbi.ucla.edu) is a database that documents experimentally determined protein-protein interactions. It provides the scientific community with an integrated set of tools for browsing and extracting information about protein interaction networks. As of September 2001, the DIP catalogs approximately 11 000 unique interactions among 5900 proteins from >80 organisms; the vast majority from yeast, Helicobacter pylori and human. Tools have been developed that allow users to analyze, visualize and integrate their own experimental data with the information about protein-protein interactions available in the DIP database.
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              The IntAct molecular interaction database in 2012

              IntAct is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. Two levels of curation are now available within the database, with both IMEx-level annotation and less detailed MIMIx-compatible entries currently supported. As from September 2011, IntAct contains approximately 275 000 curated binary interaction evidences from over 5000 publications. The IntAct website has been improved to enhance the search process and in particular the graphical display of the results. New data download formats are also available, which will facilitate the inclusion of IntAct's data in the Semantic Web. IntAct is an active contributor to the IMEx consortium (http://www.imexconsortium.org). IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.
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                Author and article information

                Journal
                Database (Oxford)
                Database (Oxford)
                databa
                databa
                Database: The Journal of Biological Databases and Curation
                Oxford University Press
                1758-0463
                2016
                02 July 2016
                02 July 2016
                : 2016
                : baw103
                Affiliations
                1School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ 85721, USA
                2Institute for Genomics, Biocomputing and Biotechnology, College of Veterinary Medicine, Institute for Genomics, Mississippi State University, Mississippi State, MS 39762, USA
                3College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762 USA
                Author notes
                * Corresponding author: Phone: 662 325 5859; Fax: 662 325 1031; Email: bnanduri@ 123456cvm.msstate.edu

                Citation details: Ammari,M.G., Gresham,C.R., McCarthy,F.M. et al. HPIDB 2.0: a curated database for host–pathogen interactions. Database (2016) Vol. 2016: article ID baw103; doi:10.1093/database/baw103

                Article
                baw103
                10.1093/database/baw103
                4930832
                27374121
                08087ca6-7254-44d5-9bf2-cddc8528e370
                © The Author(s) 2016. Published by Oxford University Press.

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

                History
                : 10 March 2016
                : 11 May 2016
                : 08 June 2016
                Page count
                Pages: 9
                Categories
                Database Update

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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