COVID-KOP: Integrating Emerging COVID-19 Data with the ROBOKOP Database.
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ABSTRACT:
SUBMITTER: Korn D
PROVIDER: S-EPMC7316095 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
Publications
COVID-KOP: Integrating Emerging COVID-19 Data with the ROBOKOP Database.
Korn Daniel D Bobrowski Tesia T Li Michael M Kebede Yaphet Y Wang Patrick P Owen Phillips P Vaidya Gaurav G Muratov Eugene E Chirkova Rada R Bizon Chris C Tropsha Alexander A
ChemRxiv : the preprint server for chemistry 20200618
In response to the COVID-19 pandemic, we established COVID-KOP, a new knowledgebase integrating the existing ROBOKOP biomedical knowledge graph with information from recent biomedical literature on COVID-19 annotated in the CORD-19 collection. COVID-KOP can be used effectively to test new hypotheses concerning repurposing of known drugs and clinical drug candidates against COVID-19. COVID-KOP is freely accessible at <a href="https://covidkop.renci.org/">https://covidkop.renci.org/</a>. For code ...[more]
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Project description:SummaryIn response to the COVID-19 pandemic, we established COVID-KOP, a new knowledgebase integrating the existing Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP) biomedical knowledge graph with information from recent biomedical literature on COVID-19 annotated in the CORD-19 collection. COVID-KOP can be used effectively to generate new hypotheses concerning repurposing of known drugs and clinical drug candidates against COVID-19 by establishing respective confirmatory pathways of drug action.Availability and implementationCOVID-KOP is freely accessible at https://covidkop.renci.org/. For code and instructions for the original ROBOKOP, see: https://github.com/NCATS-Gamma/robokop.
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Project description:BackgroundBiological processes are mediated by networks of interacting genes and proteins. Efforts to map and understand these networks are resulting in the proliferation of interaction data derived from both experimental and computational techniques for a number of organisms. The volume of this data combined with the variety of specific forms it can take has created a need for comprehensive databases that include all of the available data sets, and for exploration tools to facilitate data integration and analysis. One powerful paradigm for the navigation and analysis of interaction data is an interaction graph or map that represents proteins or genes as nodes linked by interactions. Several programs have been developed for graphical representation and analysis of interaction data, yet there remains a need for alternative programs that can provide casual users with rapid easy access to many existing and emerging data sets.DescriptionHere we describe a comprehensive database of Drosophila gene and protein interactions collected from a variety of sources, including low and high throughput screens, genetic interactions, and computational predictions. We also present a program for exploring multiple interaction data sets and for combining data from different sources. The program, referred to as the Interaction Map (IM) Browser, is a web-based application for searching and visualizing interaction data stored in a relational database system. Use of the application requires no downloads and minimal user configuration or training, thereby enabling rapid initial access to interaction data. IM Browser was designed to readily accommodate and integrate new types of interaction data as it becomes available. Moreover, all information associated with interaction measurements or predictions and the genes or proteins involved are accessible to the user. This allows combined searches and analyses based on either common or technique-specific attributes. The data can be visualized as an editable graph and all or part of the data can be downloaded for further analysis with other tools for specific applications. The database is available at http://proteome.wayne.edu/PIMdb.htmlConclusionThe Drosophila Interactions Database described here places a variety of disparate data into one easily accessible location. The database has a simple structure that maintains all relevant information about how each interaction was determined. The IM Browser provides easy, complete access to this database and could readily be used to publish other sets of interaction data. By providing access to all of the available information from a variety of data types, the program will also facilitate advanced computational analyses.
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Project description:Veterinary diagnostic laboratories derive thousands of nucleotide sequences from clinical samples of swine pathogens such as porcine reproductive and respiratory syndrome virus (PRRSV), Senecavirus A and swine enteric coronaviruses. In addition, next generation sequencing has resulted in the rapid production of full-length genomes. Presently, sequence data are released to diagnostic clients but are not publicly available as data may be associated with sensitive information. However, these data can be used for field-relevant vaccines; determining where and when pathogens are spreading; have relevance to research in molecular and comparative virology; and are a component in pandemic preparedness efforts. We have developed a centralized sequence database that integrates private clinical data using PRRSV data as an exemplar, alongside publicly available genomic information. We implemented the Tripal toolkit, a collection of Drupal modules that are used to manage, visualize and disseminate biological data stored within the Chado database schema. New sequences sourced from diagnostic laboratories contain: genomic information; date of collection; collection location; and a unique identifier. Users can download annotated genomic sequences using a customized search interface that incorporates data mined from published literature; search for similar sequences using BLAST-based tools; and explore annotated reference genomes. Additionally, custom annotation pipelines have determined species, the location of open reading frames and nonstructural proteins and the occurrence of putative frame shifts. Eighteen swine pathogens have been curated. The database provides researchers access to sequences discovered by veterinary diagnosticians, allowing for epidemiological and comparative virology studies. The result will be a better understanding on the emergence of novel swine viruses and how these novel strains are disseminated in the USA and abroad. Database URLhttps://swinepathogendb.org.
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Project description:Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. The rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. There are no drugs or other therapeutics approved by the US Food and Drug Administration to prevent or treat COVID-19: information on the disease is very limited and scattered even if it exists. This motivates the use of data integration, combining data from diverse sources and eliciting useful information with a unified view of them. In this paper, we propose a Bayesian hierarchical model that integrates global data for real-time prediction of infection trajectory for multiple countries. Because the proposed model takes advantage of borrowing information across multiple countries, it outperforms an existing individual country-based model. As fully Bayesian way has been adopted, the model provides a powerful predictive tool endowed with uncertainty quantification. Additionally, a joint variable selection technique has been integrated into the proposed modeling scheme, which aimed to identify possible country-level risk factors for severe disease due to COVID-19.
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Project description: Not available
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Project description:Novel Corona-virus Disease 2019 (nCOVID 19) is caused by a novel virulent corona virus and leads to potentially fatal virulent pneumonia and severe respiratory distress syndrome. It was initially declared as public health emergency if international concern by WHO followed by Pandemic on 12th March 2020. As of 10th April 2020, more than 1.5 million people are affected globally with around 95,000 deaths. Vaccines for this deadly virus are currently under development and many drugs used for other indications have been repurposed and investigated for prophylaxis and treatment of COVID 19. As per SOLIDARITY trial by WHO, some of the most promising candidates include chloroquine phosphate and hydroxychloroquine which are anti-malarial medications, Remdesivir, Lopinavir-Ritonavir combination with or without interferon which are anti-HIV drugs and convalescent plasma therapy. The current evidence of efficacy and ongoing research has been elaborated in the article. Besides, there has been evidence regarding inflammatory pathogenesis of this virus leading to cytokine storm in susceptible individuals. Thus, anti-proinflammatory cytokine drugs like Anakinra and Tocilizumab are undergoing multiple trials and some results are encouraging. Similarly, use of anti-inflammatory cytokines like IL-37 and IL-38 is hypothesised to be useful and is under research. The situation is still evolving and hence there is yet no definitive therapy but to conclude the use of repurposed medications can be a boon till a definitive therapy and vaccines are developed.
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Project description:Demonstration COVID-19 Data Hub Project
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