The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. 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. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. 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. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

With the high frequency and intensity of worldwide disasters, cause-related marketing campaigns with sudden disasters are becoming increasingly popular. However, little is known about whether and how cause acuteness may influence consumer attitudes. This research aims to extend this research area through investigating the relationship between cause acuteness and consumer attitudes toward the product, as well as its underlying mechanism and boundary conditions. Based on a moral psychology perspective, we propose a theoretical model focusing on the mediating role of moral (...) elevation in influencing consumer attitudes. This model also incorporates product-cause fit and information transparency as moderators underpinning necessary conditions that are likely to lead to positive consumer attitudes. Four empirical studies were conducted to test our model. Our research results reveal that consumers have more positive attitudes toward the product associated with a sudden disaster than with an ongoing tragedy. Furthermore, the positive effect of cause acuteness on consumer attitudes is mediated by enhanced moral elevation, which occurs under the conditions of high product-cause fit and high information transparency. (shrink)

The National Cancer Institute thesaurus is an important knowledge resource that should ideally be error-free. We investigated the occurrence of errors in the Neoplasm subhierarchy, which is a part...

The Chemical Entities of Biological Interest (ChEBI) ontology is an important reference for applications dealing with chemical annotations and data mining. Modeling errors and inconsistencies in th...