ArticleBMC microbiology2015
Representing virus-host interactions and other multi-organism processes in the Gene Ontology.
Article in BMC microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 22 citations in OpenAlex.
- Computational Characterization of Ligand Recognition and Inhibition in a 1,4-Dioxane-Degrading Propane Monooxygenase.Journal of chemical information and modeling · 2026Article
- New and revised gene ontology biological process terms describe multiorganism interactions critical for understanding microbial pathogenesis and sequences of concern.Journal of biomedical semantics · 2025Article
- Annotation of Functions of Sequences of Concern and Its Relevance to the New Biosecurity Regulatory Framework in the United States.Applied biosafety : journal of the American Biological Safety Association · 2024Article
- Article
- Stress Decreases Host Viral Resistance and Increases Covid Susceptibility in Embryonic Stem Cells.Stem cell reviews and reports · 2021Article
- Alignment of biological networks by integer linear programming: virus-host protein-protein interaction networks.BMC bioinformatics · 2020Article
- A systems approach to infectious disease.Nature reviews. Genetics · 2020Review
- COVID-19 Virulence in Aged Patients Might Be Impacted by the Host Cellular MicroRNAs Abundance/Profile.Aging and disease · 2020Article
- Resources to Discover and Use Short Linear Motifs in Viral Proteins.Trends in biotechnology · 2020Review
- RNA-Seq-Based Whole Transcriptome Analysis of IPEC-J2 Cells During Swine Acute Diarrhea Syndrome Coronavirus Infection.Frontiers in veterinary science · 2020Article
- Identification of ceRNA network based on a RNA-seq shows prognostic lncRNA biomarkers in human lung adenocarcinoma.Oncology letters · 2018Article
- Exploring autophagy with Gene Ontology.Autophagy · 2018Review
- The ins and outs of eukaryotic viruses: Knowledge base and ontology of a viral infection.PloS one · 2017Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundThe Gene Ontology project is a collaborative effort to provide descriptions of gene products in a consistent and computable language, and in a species-independent manner. The Gene Ontology is designed to be applicable to all organisms but up to now has been largely under-utilized for prokaryotes and viruses, in part because of a lack of appropriate ontology terms.
methodsTo address this issue, we have developed a set of Gene Ontology classes that are applicable to microbes and their hosts, improving both coverage and quality in this area of the Gene Ontology. Describing microbial and viral gene products brings with it the additional challenge of capturing both the host and the microbe. Recognising this, we have worked closely with annotation groups to test and optimize the GO classes, and we describe here a set of annotation guidelines that allow the controlled description of two interacting organisms.
conclusionsBuilding on the microbial resources already in existence such as ViralZone, UniProtKB keywords and MeGO, this project provides an integrated ontology to describe interactions between microbial species and their hosts, with mappings to the external resources above. Housing this information within the freely-accessible Gene Ontology project allows the classes and annotation structure to be utilized by a large community of biologists and users.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.