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      Literature-Based Enrichment Insights into Redox Control of Vascular Biology

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          Abstract

          In cellular physiology and signaling, reactive oxygen species (ROS) play one of the most critical roles. ROS overproduction leads to cellular oxidative stress. This may lead to an irrecoverable imbalance of redox (oxidation-reduction reaction) function that deregulates redox homeostasis, which itself could lead to several diseases including neurodegenerative disease, cardiovascular disease, and cancers. In this study, we focus on the redox effects related to vascular systems in mammals. To support research in this domain, we developed an online knowledge base, DES-RedoxVasc, which enables exploration of information contained in the biomedical scientific literature. The DES-RedoxVasc system analyzed 233399 documents consisting of PubMed abstracts and PubMed Central full-text articles related to different aspects of redox biology in vascular systems. It allows researchers to explore enriched concepts from 28 curated thematic dictionaries, as well as literature-derived potential associations of pairs of such enriched concepts, where associations themselves are statistically enriched. For example, the system allows exploration of associations of pathways, diseases, mutations, genes/proteins, miRNAs, long ncRNAs, toxins, drugs, biological processes, molecular functions, etc. that allow for insights about different aspects of redox effects and control of processes related to the vascular system. Moreover, we deliver case studies about some existing or possibly novel knowledge regarding redox of vascular biology demonstrating the usefulness of DES-RedoxVasc. DES-RedoxVasc is the first compiled knowledge base using text mining for the exploration of this topic.

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          Most cited references122

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          LMSD: LIPID MAPS structure database

          The LIPID MAPS Structure Database (LMSD) is a relational database encompassing structures and annotations of biologically relevant lipids. Structures of lipids in the database come from four sources: (i) LIPID MAPS Consortium's core laboratories and partners; (ii) lipids identified by LIPID MAPS experiments; (iii) computationally generated structures for appropriate lipid classes; (iv) biologically relevant lipids manually curated from LIPID BANK, LIPIDAT and other public sources. All the lipid structures in LMSD are drawn in a consistent fashion. In addition to a classification-based retrieval of lipids, users can search LMSD using either text-based or structure-based search options. The text-based search implementation supports data retrieval by any combination of these data fields: LIPID MAPS ID, systematic or common name, mass, formula, category, main class, and subclass data fields. The structure-based search, in conjunction with optional data fields, provides the capability to perform a substructure search or exact match for the structure drawn by the user. Search results, in addition to structure and annotations, also include relevant links to external databases. The LMSD is publicly available at
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            Uberon, an integrative multi-species anatomy ontology

            We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.org
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              The PANTHER database of protein families, subfamilies, functions and pathways

              PANTHER is a large collection of protein families that have been subdivided into functionally related subfamilies, using human expertise. These subfamilies model the divergence of specific functions within protein families, allowing more accurate association with function (ontology terms and pathways), as well as inference of amino acids important for functional specificity. Hidden Markov models (HMMs) are built for each family and subfamily for classifying additional protein sequences. The latest version, 5.0, contains 6683 protein families, divided into 31 705 subfamilies, covering ∼90% of mammalian protein-coding genes. PANTHER 5.0 includes a number of significant improvements over previous versions, most notably (i) representation of pathways (primarily signaling pathways) and association with subfamilies and individual protein sequences; (ii) an improved methodology for defining the PANTHER families and subfamilies, and for building the HMMs; (iii) resources for scoring sequences against PANTHER HMMs both over the web and locally; and (iv) a number of new web resources to facilitate analysis of large gene lists, including data generated from high-throughput expression experiments. Efforts are underway to add PANTHER to the InterPro suite of databases, and to make PANTHER consistent with the PIRSF database. PANTHER is now publicly available without restriction at http://panther.appliedbiosystems.com.
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                Author and article information

                Contributors
                Journal
                Oxid Med Cell Longev
                Oxid Med Cell Longev
                OMCL
                Oxidative Medicine and Cellular Longevity
                Hindawi
                1942-0900
                1942-0994
                2019
                16 May 2019
                : 2019
                : 1769437
                Affiliations
                1King Abdullah University of Science and Technology, Computational Bioscience Research Center, Thuwal, Saudi Arabia
                2Vinca Institute, University of Belgrade, Laboratory for Molecular Endocrinology and Radiobiology, Belgrade, Serbia
                Author notes

                Academic Editor: Andreas Daiber

                Author information
                http://orcid.org/0000-0003-2709-5356
                http://orcid.org/0000-0003-1513-2762
                http://orcid.org/0000-0003-3952-7363
                http://orcid.org/0000-0001-8482-2172
                http://orcid.org/0000-0002-5958-5731
                http://orcid.org/0000-0001-5435-4750
                http://orcid.org/0000-0002-0012-2636
                Article
                10.1155/2019/1769437
                6542245
                48b812b7-a610-42fd-b736-370bf9ec3a2f
                Copyright © 2019 Magbubah Essack et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 7 January 2019
                : 11 April 2019
                : 2 May 2019
                Funding
                Funded by: King Abdullah University of Science and Technology
                Award ID: FCC/1/1976-24-01
                Award ID: BAS/1/1606-01-01
                Funded by: Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja
                Award ID: 173034
                Award ID: 173033
                Categories
                Review Article

                Molecular medicine
                Molecular medicine

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