A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology

[1]  H. Tettelin,et al.  COVID-19 vaccine design using reverse and structural vaccinology, ontology-based literature mining and machine learning , 2022, Briefings Bioinform..

[2]  O. Choudhary,et al.  Delta variant (B.1.617.2) of SARS-CoV-2: Mutations, impact, challenges and possible solutions , 2022, Human vaccines & immunotherapeutics.

[3]  Shu Wan,et al.  SARS-CoV-2 Omicron variant: recent progress and future perspectives , 2022, Signal Transduction and Targeted Therapy.

[4]  N. Hulo,et al.  Infectious viral load in unvaccinated and vaccinated individuals infected with ancestral, Delta or Omicron SARS-CoV-2 , 2022, Nature Medicine.

[5]  Zhendong Li,et al.  Mutational Effect of Some Major COVID-19 Variants on Binding of the S Protein to ACE2 , 2022, Biomolecules.

[6]  S. Mallapaty.  COVID-19: How Omicron overtook Delta in three charts. , 2022, Nature.

[7]  Sameer Phalke,et al.  SARS-CoV-2 Mutations and Their Impact on Diagnostics, Therapeutics and Vaccines , 2022, Frontiers in Medicine.

[8]  Ke-wen Jiang,et al.  Dihydroartemisinin attenuates pulmonary inflammation and fibrosis in rats by suppressing JAK2/STAT3 signaling , 2022, Aging.

[9]  Hong Yu,et al.  Differential COVID-19 Symptoms Given Pandemic Locations, Time, and Comorbidities During the Early Pandemic , 2022, Frontiers in Medicine.

[10]  J. Ramos-Rincón,et al.  Exposure to valproic acid is associated with less pulmonary infiltrates and improvements in diverse clinical outcomes and laboratory parameters in patients hospitalized with COVID-19 , 2022, PloS one.

[11]  Mohamed Ali Hadj Taieb,et al.  Representing COVID-19 information in collaborative knowledge graphs: The case of Wikidata , 2021, Semantic Web.

[12]  Graham W. Taylor,et al.  SARS-CoV-2 evolution during treatment of chronic infection , 2021, Nature.

[13]  Kimihito Ito,et al.  Relative instantaneous reproduction number of Omicron SARS‐CoV‐2 variant with respect to the Delta variant in Denmark , 2021, Journal of medical virology.

[14]  S. Byrareddy,et al.  Omicron SARS-CoV-2 variant: Unique features and their impact on pre-existing antibodies , 2021, Journal of Autoimmunity.

[15]  Fan Tong,et al.  COVID19-OBKG: An Ontology-Based Knowledge Graph and Web Service for COVID-19 , 2021, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[16]  Y. He,et al.  Cov19VaxKB: A web-based integrative COVID-19 vaccine knowledge base , 2021, Vaccine: X.

[17]  Andrew E. Williams,et al.  An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C) , 2021, J. Am. Medical Informatics Assoc..

[18]  N. Ferguson,et al.  Community transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated individuals in the UK: a prospective, longitudinal, cohort study , 2021, The Lancet Infectious Diseases.

[19]  A. Masci,et al.  CIDO ontology updates and secondary analysis of host responses to COVID-19 infection based on ImmPort reports and literature , 2021, Journal of Biomedical Semantics.

[20]  JITHIN VISHNU,et al.  Antiviral properties of copper and its alloys to inactivate covid-19 virus: a review , 2021, BioMetals.

[21]  Y. Liu,et al.  The reproductive number of the Delta variant of SARS-CoV-2 is far higher compared to the ancestral SARS-CoV-2 virus , 2021, Journal of travel medicine.

[22]  Haibo Wu,et al.  Nucleocapsid mutations R203K/G204R increase the infectivity, fitness, and virulence of SARS-CoV-2 , 2021, Cell Host & Microbe.

[23]  A. Pavesi.  Prediction of two novel overlapping ORFs in the genome of SARS-CoV-2 , 2021, Virology.

[24]  Y. Perl,et al.  Visual comprehension and orientation into the COVID-19 CIDO ontology , 2021, Journal of Biomedical Informatics.

[25]  E. Zaslavsky,et al.  Advances in the computational landscape for repurposed drugs against COVID-19 , 2021, Drug Discovery Today.

[26]  Y. He,et al.  Precision omics data integration and analysis with interoperable ontologies and their application for COVID-19 research. , 2021, Briefings in functional genomics.

[27]  R. Prasad,et al.  Potential molecular mechanisms of zinc- and copper-mediated antiviral activity on COVID-19 , 2021, Nutrition Research.

[28]  S. Jahanfar,et al.  Characterization of SARS-CoV-2 different variants and related morbidity and mortality: a systematic review , 2021, European Journal of Medical Research.

[29]  Y. He,et al.  Integrative web-based analysis of omics data for study of drugs against SARS-CoV-2 , 2021, Scientific Reports.

[30]  Yufang Shi,et al.  Syncytia formation during SARS-CoV-2 lung infection: a disastrous unity to eliminate lymphocytes , 2021, Cell Death & Differentiation.

[31]  Irwin Jungreis,et al.  SARS-CoV-2 gene content and COVID-19 mutation impact by comparing 44 Sarbecovirus genomes , 2021, Nature Communications.

[32]  R. Kaladevi,et al.  Semantic and NLP‐Based Retrieval From Covid‐19 Ontology , 2021, Machine Learning for Healthcare Applications.

[33]  Maxwell I. Zimmerman,et al.  The SARS-CoV-2 nucleocapsid protein is dynamic, disordered, and phase separates with RNA , 2021, Nature Communications.

[34]  M. Beltramello,et al.  N-terminal domain antigenic mapping reveals a site of vulnerability for SARS-CoV-2 , 2021, Cell.

[35]  D. Fidock,et al.  Artemisia annua L. extracts inhibit the in vitro replication of SARS-CoV-2 and two of its variants , 2021, Journal of Ethnopharmacology.

[36]  F. Yoshimoto.  A Biochemical Perspective of the Nonstructural Proteins (NSPs) and the Spike Protein of SARS CoV-2 , 2021, The Protein Journal.

[37]  M. Nussenzweig,et al.  mRNA vaccine-elicited antibodies to SARS-CoV-2 and circulating variants , 2021, Nature.

[38]  M. Nussenzweig,et al.  mRNA vaccine-elicited antibodies to SARS-CoV-2 and circulating variants , 2021, bioRxiv.

[39]  Hong Yu,et al.  Ontological modeling and analysis of experimentally or clinically verified drugs against coronavirus infection , 2021, Scientific Data.

[40]  Christopher G Chute,et al.  The Human Phenotype Ontology in 2021 , 2020, Nucleic Acids Res..

[41]  Peter B. McGarvey,et al.  UniProt: the universal protein knowledgebase in 2021 , 2020, Nucleic Acids Res..

[42]  Zhiyong Lu,et al.  LitCovid: an open database of COVID-19 literature , 2020, Nucleic Acids Res..

[43]  Philip R. O. Payne,et al.  The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment , 2020, J. Am. Medical Informatics Assoc..

[44]  Lindsay G. Cowell,et al.  The Infectious Disease Ontology in the age of COVID-19 , 2020, J. Biomed. Semant..

[45]  William D. Duncan,et al.  A Community Effort for COVID-19 Ontology Harmonization , 2021, ICBO.

[46]  W. Ju,et al.  Ontology-based Modeling, Representation, and Analysis of Biomarkers in Healthy and Disease Kidney Tissue , 2021, ICBO.

[47]  Y. He,et al.  Ontology Modeling and Analysis of COVID-19-associated Acute Kidney Injury and Its Underlying Molecular Mechanisms , 2021, ICBO.

[48]  Y. He,et al.  Identification and Ontology Term Enrichment Analysis of Genes Associated with COVID-19 and Acute Kidney Disease , 2021, ICBO.

[49]  OUP accepted manuscript , 2021, Nucleic Acids Research.

[50]  Haiyong Peng,et al.  SARS-CoV-2 spike-protein D614G mutation increases virion spike density and infectivity , 2020, Nature Communications.

[51]  F. Burgos,et al.  Respiratory function in patients post-infection by COVID-19: a systematic review and meta-analysis , 2020, Pulmonology.

[52]  R. Shetty,et al.  R0 and Re of COVID-19: Can We Predict When the Pandemic Outbreak will be Contained? , 2020, Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine.

[53]  Lucy Lu Wang,et al.  Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project , 2020, Nature Reviews Nephrology.

[54]  Distinct RT-PCR diagnosis profiles of father and son patients of COVID-19 using nasopharyngeal and alveolar lavage fluid samples , 2020, Inflammation and Cell Signaling.

[55]  J. Zuniga,et al.  The use of copper to help prevent transmission of SARS-coronavirus and influenza viruses. A general review , 2020, Diagnostic Microbiology and Infectious Disease.

[56]  Edward C. Holmes,et al.  A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology , 2020, Nature Microbiology.

[57]  Lee-Jen Wei,et al.  Remdesivir for the Treatment of Covid-19 - Preliminary Report. , 2020, The New England journal of medicine.

[58]  A. Peleg,et al.  Remdesivir for the Treatment of Covid-19 - Preliminary Report. , 2020, The New England journal of medicine.

[59]  Mei U Wong,et al.  COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning , 2020, Frontiers in Immunology.

[60]  Robert D. Finn,et al.  COVID-19 pandemic reveals the peril of ignoring metadata standards , 2020, Scientific Data.

[61]  Marta Tatu,et al.  Ten ways of leveraging ontologies for natural language processing and its enterprise applications , 2020, SBD@SIGMOD.

[62]  Yang Wang,et al.  CIDO, a community-based ontology for coronavirus disease knowledge and data integration, sharing, and analysis , 2020, Scientific Data.

[63]  B. Rahman,et al.  The basic reproduction number of SARS‐CoV‐2 in Wuhan is about to die out, how about the rest of the World? , 2020, Reviews in medical virology.

[64]  Benjamin J. Polacco,et al.  A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing , 2020, Nature.

[65]  Vitória S. Foletto,et al.  Drug repositioning is an alternative for the treatment of coronavirus COVID-19 , 2020, International Journal of Antimicrobial Agents.

[66]  M. Sehailia,et al.  Antimalarial-agent artemisinin and derivatives portray more potent binding to Lys353 and Lys31-binding hotspots of SARS-CoV-2 spike protein than hydroxychloroquine: potential repurposing of artenimol for COVID-19 , 2020, Journal of biomolecular structure & dynamics.

[67]  Jonathan E. Schmitz,et al.  Laboratory Diagnosis of COVID-19: Current Issues and Challenges , 2020, Journal of Clinical Microbiology.

[68]  Hong Yu,et al.  Ontological and Bioinformatic Analysis of Anti-Coronavirus Drugs and Their Implication for Drug Repurposing against COVID-19 , 2020 .

[69]  Trey Ideker,et al.  A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing , 2020, bioRxiv.

[70]  F. Cheng,et al.  Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2 , 2020, Cell Discovery.

[71]  S. Pascarella,et al.  COVID‐2019: The role of the nsp2 and nsp3 in its pathogenesis , 2020, Journal of medical virology.

[72]  L. Saif,et al.  Emerging Viruses without Borders: The Wuhan Coronavirus , 2020, Viruses.

[73]  Michael J. Loeffelholz,et al.  Laboratory diagnosis of emerging human coronavirus infections – the state of the art , 2020, Emerging microbes & infections.

[74]  Robert Hoehndorf,et al.  Ontology based mining of pathogen–disease associations from literature , 2019, Journal of biomedical semantics.

[75]  S. Cauchemez,et al.  Comparative Analysis of Eleven Healthcare-Associated Outbreaks of Middle East Respiratory Syndrome Coronavirus (Mers-Cov) from 2015 to 2017 , 2019, Scientific Reports.

[76]  Yurii S. Moroz,et al.  Ultra-large library docking for discovering new chemotypes , 2019, Nature.

[77]  Kara Dolinski,et al.  The BioGRID interaction database: 2019 update , 2018, Nucleic Acids Res..

[78]  Xin Gao,et al.  OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction , 2018, Bioinform..

[79]  S. Mooney,et al.  OPMI: the Ontology of Precision Medicine and Investigation and its Support for Clinical Data and Metadata Representation and Analysis , 2019, ICBO.

[80]  V. Persico.  Big Data for Health , 2019, Encyclopedia of Big Data Technologies.

[81]  James A. Overton,et al.  The eXtensible ontology development (XOD) principles and tool implementation to support ontology interoperability , 2018, J. Biomed. Semant..

[82]  David S. Wishart,et al.  DrugBank 5.0: a major update to the DrugBank database for 2018 , 2017, Nucleic Acids Res..

[83]  Yuelong Shu,et al.  GISAID: Global initiative on sharing all influenza data – from vision to reality , 2017, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[84]  Arzucan Özgür,et al.  Ontology-based literature mining of E. coli vaccine-associated gene interaction networks , 2017, Journal of Biomedical Semantics.

[85]  Werner Ceusters,et al.  A Realism-Based View on Counts in OMOP's Common Data Model , 2017, pHealth.

[86]  Arzucan Özgür,et al.  The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature , 2016, BioData Mining.

[87]  James Geller,et al.  A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies , 2016, J. Biomed. Informatics.

[88]  Erik Schultes,et al.  The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.

[89]  Christoph Steinbeck,et al.  ChEBI in 2016: Improved services and an expanding collection of metabolites , 2015, Nucleic Acids Res..

[90]  Jessica A. Turner,et al.  The Ontology for Biomedical Investigations , 2016, PloS one.

[91]  Robert Arp,et al.  Building Ontologies with Basic Formal Ontology , 2015 .

[92]  Peter N. Robinson,et al.  The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease , 2015, American journal of human genetics.

[93]  Mark A. Musen,et al.  The protégé project: a look back and a look forward , 2015, SIGAI.

[94]  Y. He,et al.  Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns , 2015, J. Biomed. Semant..

[95]  Arzucan Özgür,et al.  Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions , 2015, Journal of Biomedical Semantics.

[96]  Tatiana A. Tatusova,et al.  Gene: a gene-centered information resource at NCBI , 2014, Nucleic Acids Res..

[97]  Mathias Brochhausen,et al.  Building a drug ontology based on RxNorm and other sources , 2013, VDOS+DO@ICBO.

[98]  Winston Haynes,et al.  Unraveling the Complexities of Life Sciences Data , 2013, Big Data.

[99]  D. Barends,et al.  Biowaiver monographs for immediate release solid oral dosage forms: mefloquine hydrochloride. , 2011, Journal of pharmaceutical sciences.

[100]  E. Mohammadi,et al.  Barriers and facilitators related to the implementation of a physiological track and trigger system: A systematic review of the qualitative evidence , 2017, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[101]  Gang Feng,et al.  Disease Ontology: a backbone for disease semantic integration , 2011, Nucleic Acids Res..

[102]  Michel Dumontier,et al.  Interoperability between Biomedical Ontologies through Relation Expansion, Upper-Level Ontologies and Automatic Reasoning , 2011, PloS one.

[103]  Bernard De Baets,et al.  Reasoning with bio-ontologies: using relational closure rules to enable practical querying , 2011, Bioinform..

[104]  Dragomir R. Radev,et al.  Mining of vaccine-associated IFN-γ gene interaction networks using the Vaccine Ontology , 2011, J. Biomed. Semant..

[105]  Ryan R Brinkman,et al.  OntoFox: web-based support for ontology reuse , 2010, BMC Research Notes.

[106]  W. Lu,et al.  Severe acute respiratory syndrome coronavirus accessory protein 9b is a virion-associated protein , 2009, Virology.

[107]  Adam D. Schuyler,et al.  SciMiner: web-based literature mining tool for target identification and functional enrichment analysis , 2009, Bioinform..

[108]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

[109]  S. Trent Rosenbloom,et al.  SNOMED CT®: Utility for a General Medical Evaluation Template , 2006, AMIA.

[110]  Rafael E. Riveros,et al.  Studies in Health Technology and Informatics , 2005 .

[111]  S. Trent Rosenbloom,et al.  VA National Drug File Reference Terminology: A Cross-Institutional Content Coverage Study , 2004, MedInfo.

[112]  Olivier Bodenreider,et al.  The Unified Medical Language System (UMLS): integrating biomedical terminology , 2004, Nucleic Acids Res..

[113]  Revised U.S. surveillance case definition for severe acute respiratory syndrome (SARS) and update on SARS cases--United States and worldwide, December 2003. , 2003, MMWR. Morbidity and mortality weekly report.

[114]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

[115]  C E Lipscomb,et al.  Medical Subject Headings (MeSH). , 2000, Bulletin of the Medical Library Association.

[116]  E. Brown,et al.  The Medical Dictionary for Regulatory Activities (MedDRA) , 1999, Drug safety.

[117]  C. Nevill,et al.  A comparison of amodiaquine and chloroquine in the treatment therapy of falciparum malaria in Kenya. , 1994, East African Medical Journal.