Publications by authors named "Anita R Caron"
Article Synopsis
- The use of well-structured ontologies and ontology-aware tools enhances data and analyses to be FAIR (Findable, Accessible, Interoperable, Reusable), supporting effective lexical searches and biologically meaningful annotation grouping.
- Researchers face challenges in adopting ontologies, primarily due to their complexity and the tendency to create simplified hierarchies that may misuse relationship types, leading to ineffective organization.
- A suite of validation tools is introduced to help users align their hierarchies with established ontology structures, providing graphical reports and tailored views for various atlases like the HuBMAP Human Reference Atlas and the Human Developmental Cell Atlas.
Article Synopsis
- Phenotypic data helps us understand how genomic variations affect living organisms and is vital for clinical applications like diagnosing diseases and developing treatments.
- The field of phenomics aims to unify and analyze the vast amounts of phenotypic data collected over time, but faces challenges due to inconsistent methods and vocabularies used to record this information.
- The Unified Phenotype Ontology (uPheno) framework offers a solution by providing a standardized system for organizing phenotype terms, allowing for better integration of data across different species and improving research on genotype-phenotype associations.
Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research.
View Article and Find Full Text PDFExisting phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications.
View Article and Find Full Text PDFThe Human Reference Atlas (HRA) is defined as a comprehensive, three-dimensional (3D) atlas of all the cells in the healthy human body. It is compiled by an international team of experts who develop standard terminologies that they link to 3D reference objects, describing anatomical structures. The third HRA release (v1.
View Article and Find Full Text PDFExisting phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focused measurable trait data. Moreover, variations in gene expression in response to environmental disturbances even without any genetic alterations can also be associated with particular biological attributes.
View Article and Find Full Text PDFSimilar to managing software packages, managing the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking and dependency management. To manage these processes, a diverse set of tools is required, from command-line utilities to powerful ontology-engineering environmentsr. Particularly in the biomedical domain, which has developed a set of highly diverse yet inter-dependent ontologies, standardizing release practices and metadata and establishing shared quality standards are crucial to enable interoperability.
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