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Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. The Coronavirus Infectious Disease Ontology CIDO is a community-based ontology that supports coronavirus disease knowledge and data standardization, integration, sharing, and analysis.

Cido

Journal of Biomedical Semantics volume 13 , Article number: 25 Cite this article. Metrics details. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing NLP and clinical data integration. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. Coronavirus diseases pose major challenges to public health. As of April 27, , the number of COVID confirmed cases has risen to over million confirmed cases, resulting in over 6 million deaths globally. The dramatic increase of COVIDrelated cases and deaths over 2 years illustrates the urgent need for collaborative research on coronavirus diseases, especially COVID, by researchers around the world. These research articles cover various domains such as etiology, epidemiology, and biotechnology. During this time, many novel and repurposed medical treatments were developed and authorized to treat or prevent COVID However, the emergence of new SARS-CoV-2 variants with unique traits prompted novel research investigating the fundamental molecular mechanisms of virulence and transmission associated with these variants [ 9 ]. Throughout the COVID pandemic, epidemiological data from across the globe has been collected for viral sequences and human demographics.

This particular diagnostic testing kit can utilize 6 specimen types, as again cido in Fig.

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These coronavirus outbreaks have made us realize the critical importance of systematically studying these coronavirus infectious diseases using the cutting edge technologies. Ontology provides a unique angle to study the coronavirus infectious diseases. The Ontology of Coronavirus Infectious Disease CIDO is a community-driven open-source biomedical ontology in the area of coronavirus infectious disease. The CIDO is developed to provide standardized human- and computer-interpretable annotation and representation of various coronavirus infectious diseases, including their etiology, transmission, epidemiology, pathogenesis, diagnosis, prevention, and treatment. CIDO was initiated and co-led by Dr. Yang Wang M. Many researchers in the University of Michigan, including Dr. Brian Athey and Dr.

Cido

Journal of Biomedical Semantics volume 13 , Article number: 25 Cite this article. Metrics details. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. The scope of CIDO was evaluated by visual analysis supported by a summarization network method.

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Lancet Infect Dis. The dramatic increase of COVIDrelated cases and deaths over 2 years illustrates the urgent need for collaborative research on coronavirus diseases, especially COVID, by researchers around the world. A full comparison between PR, RefSeq, and UniProtKB is given in Supplemental Table 3 with respect to accessions, genes, and names used protein length and evidence for existence are also presented. Data 3 , ENG LV. About this article. Ethics declarations Ethics approval and consent to participate Not applicable. Training of Trainers for the iDove project, OntoFox: web-based support for ontology reuse. Shu Y, McCauley J. Deeper modeling and representation of the intricate host-virus-drug interactions would help us in better drug repurposing analysis.

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The identified terms were then mapped to the codes represented in CIDO. Evaluation of research in biomedical ontologies. Interestingly, all the three drugs, Paxlovid consisting of nirmatrelvir and ritonavir , Molnupiravir, and Remdesivir function by inhibiting enzymes responsible for coronavirus replication. However, the above framework does not work well for describing characteristic deletions or other mutation events. In addition, the infected patient will display different phenotypes after manifesting the disease, and such phenotypes may be associated with other patient attributes e. The ontology support is an ongoing project. Article Google Scholar Whetzel, P. Figure 1 lays out the high-level hierarchical structure of CIDO and shows the various imported external ontologies. Control CfD, Prevention. Our ontology development is primarily task-focused and use-case driven. Provided by the Springer Nature SharedIt content-sharing initiative. Our ontological representation, classification, and analysis of these drugs yielded many potentially valuable scientific insights. A visual evolution analysis of CIDO was performed.