2,482 research outputs found
Coordinating virus research: The Virus Infectious Disease Ontology
The COVID-19 pandemic prompted immense work on the investigation of the SARS-CoV-2 virus. Rapid, accurate, and consistent interpretation of generated data is thereby of fundamental concern. Ontologies––structured, controlled, vocabularies––are designed to support consistency of interpretation, and thereby to prevent the development of data silos. This paper describes how ontologies are serving this purpose in the COVID-19 research domain, by following principles of the Open Biological and Biomedical Ontology (OBO) Foundry and by reusing existing ontologies such as the Infectious Disease Ontology (IDO) Core, which provides terminological content common to investigations of all infectious diseases. We report here on the development of an IDO extension, the Virus Infectious Disease Ontology (VIDO), a reference ontology covering viral infectious diseases. We motivate term and definition choices, showcase reuse of terms from existing OBO ontologies, illustrate how ontological decisions were motivated by relevant life science research, and connect VIDO to the Coronavirus Infectious Disease Ontology (CIDO). We next use terms from these ontologies to annotate selections from life science research on SARS-CoV-2, highlighting how ontologies employing a common upper-level vocabulary may be seamlessly interwoven. Finally, we outline future work, including bacteria and fungus infectious disease reference ontologies currently under development, then cite uses of VIDO and CIDO in host-pathogen data analytics, electronic health record annotation, and ontology conflict-resolution projects
The Human Phenotype Ontology in 2024: phenotypes around the world.
The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs
A clinical decision support system for detecting and mitigating potentially inappropriate medications
Background: Medication errors are a leading cause of preventable harm to patients. In older adults, the impact of ageing on the therapeutic effectiveness and safety of drugs is a significant concern, especially for those over 65. Consequently, certain medications called Potentially Inappropriate Medications (PIMs) can be dangerous in the elderly and should be avoided. Tackling PIMs by health professionals and patients can be time-consuming and error-prone, as the criteria underlying the definition of PIMs are complex and subject to frequent updates. Moreover, the criteria are not available in a representation that health systems can interpret and reason with directly.
Objectives: This thesis aims to demonstrate the feasibility of using an ontology/rule-based approach in a clinical knowledge base to identify potentially inappropriate medication(PIM). In addition, how constraint solvers can be used effectively to suggest alternative medications and administration schedules to solve or minimise PIM undesirable side effects.
Methodology: To address these objectives, we propose a novel integrated approach using formal rules to represent the PIMs criteria and inference engines to perform the reasoning presented in the context of a Clinical Decision Support System (CDSS). The approach aims to detect, solve, or minimise undesirable side-effects of PIMs through an ontology (knowledge base) and inference engines incorporating multiple reasoning approaches.
Contributions: The main contribution lies in the framework to formalise PIMs, including the steps required to define guideline requisites to create inference rules to detect and propose alternative drugs to inappropriate medications. No formalisation of the selected guideline (Beers Criteria) can be found in the literature, and hence, this thesis provides a novel ontology for it. Moreover, our process of minimising undesirable side effects offers a novel approach that enhances and optimises the drug rescheduling process, providing a more accurate way to minimise the effect of drug interactions in clinical practice
The experience of using role-play and simulated practice as an adjunct to paramedic placement learning
This study examines the current experiences of paramedic students regarding the perceptions, understanding and utilisation of role-play plus simulation in a paramedic degree programme. This area is underexplored, so it is situated in the context of paramedic practice, training and education landscape in UK, Australia, Canada and the USA, and cognate professions.The skills training in its original format remains, as does the on-the job clinical training (hospital placement and ambulance internship) as these are set regulatory requirements. Role-play and task focused simulation is used as part of syndicate learning for skills development. A mixed methodology, comprising both qualitative and quantitative approaches, including an exploratory sequential design, was used in this research. This was done in order to evaluate the student perceptions of their current placement experience and to explore the perception of combining simulation and role-playing.The study results show that the current educational model of clinical placement is flawed. After a brief exposure to an exemplar event, students preferred the combination of simulation and role-playing over the use of either technique independently. Adoption of this technique firstly requires a set definition of terminology and consistent interpretation within the discipline.A consolidation of the students’ experience is required by enhancing the mentorship supports. Further research is needed to design and develop the combination of role-playing and simulation to enhance student learning in the simulation laboratory. This study promotes positive social change by providing data to the educators and key decision makers of the paramedic programme on students’ perceptions of the benefits of a technique that is able to support instruction and augment the students’ clinical placement experience
The Human Phenotype Ontology in 2024: phenotypes around the world
\ua9 The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs
Sound Event Detection by Exploring Audio Sequence Modelling
Everyday sounds in real-world environments are a powerful source of information by which humans can interact with their environments. Humans can infer what is happening around them by listening to everyday sounds. At the same time, it is a challenging task for a computer algorithm in a smart device to automatically recognise, understand, and interpret everyday sounds. Sound event detection (SED) is the process of transcribing an audio recording into sound event tags with onset and offset time values. This involves classification and segmentation of sound events in the given audio recording. SED has numerous applications in everyday life which include security and surveillance, automation, healthcare monitoring, multimedia information retrieval, and assisted living technologies. SED is to everyday sounds what automatic speech recognition (ASR) is to speech and automatic music transcription (AMT) is to music. The fundamental questions in designing a sound recognition system are, which portion of a sound event should the system analyse, and what proportion of a sound event should the system process in order to claim a confident detection of that particular sound event. While the classification of sound events has improved a lot in recent years, it is considered that the temporal-segmentation of sound events has not improved in the same extent. The aim of this thesis is to propose and develop methods to improve the segmentation and classification of everyday sound events in SED models. In particular, this thesis explores the segmentation of sound events by investigating audio sequence encoding-based and audio sequence modelling-based methods, in an effort to improve the overall sound event detection performance. In the first phase of this thesis, efforts are put towards improving sound event detection by explicitly conditioning the audio sequence representations of an SED model using sound activity detection (SAD) and onset detection. To achieve this, we propose multi-task learning-based SED models in which SAD and onset detection are used as auxiliary tasks for the SED task. The next part of this thesis explores self-attention-based audio sequence modelling, which aggregates audio representations based on temporal relations within and between sound events, scored on the basis of the similarity of sound event portions in audio event sequences. We propose SED models that include memory-controlled, adaptive, dynamic, and source separation-induced self-attention variants, with the aim to improve overall sound recognition
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Selective Constraints in Experimentally Defined Primate Regulatory Regions
Changes in gene regulation may be important in evolution. However, the evolutionary properties of regulatory mutations are currently poorly understood. This is partly the result of an incomplete annotation of functional regulatory DNA in many species. For example, transcription factor binding sites (TFBSs), a major component of eukaryotic regulatory architecture, are typically short, degenerate, and therefore difficult to differentiate from randomly occurring, nonfunctional sequences. Furthermore, although sites such as TFBSs can be computationally predicted using evolutionary conservation as a criterion, estimates of the true level of selective constraint (defined as the fraction of strongly deleterious mutations occurring at a locus) in regulatory regions will, by definition, be upwardly biased in datasets that are a priori evolutionarily conserved. Here we investigate the fitness effects of regulatory mutations using two complementary datasets of human TFBSs that are likely to be relatively free of ascertainment bias with respect to evolutionary conservation but, importantly, are supported by experimental data. The first is a collection of almost >2,100 human TFBSs drawn from the literature in the TRANSFAC database, and the second is derived from several recent high-throughput chromatin immunoprecipitation coupled with genomic microarray (ChIP-chip) analyses. We also define a set of putative cis-regulatory modules (pCRMs) by spatially clustering multiple TFBSs that regulate the same gene. We find that a relatively high proportion (∼37%) of mutations at TFBSs are strongly deleterious, similar to that at a 2-fold degenerate protein-coding site. However, constraint is significantly reduced in human and chimpanzee pCRMS and ChIP-chip sequences, relative to macaques. We estimate that the fraction of regulatory mutations that have been driven to fixation by positive selection in humans is not significantly different from zero. We also find that the level of selective constraint in our TFBSs, pCRMs, and ChIP-chip sequences is negatively correlated with the expression breadth of the regulated gene, whereas the opposite relationship holds at that gene's nonsynonymous and synonymous sites. Finally, we find that the rate of protein evolution in a transcription factor appears to be positively correlated with the breadth of expression of the gene it regulates. Our study suggests that strongly deleterious regulatory mutations are considerably more likely (1.6-fold) to occur in tissue-specific than in housekeeping genes, implying that there is a fitness cost to increasing “complexity” of gene expression.</p
Talking about personal recovery in bipolar disorder: Integrating health research, natural language processing, and corpus linguistics to analyse peer online support forum posts
Background: Personal recovery, ‘living a satisfying, hopeful and contributing lifeeven with the limitations caused by the illness’ (Anthony, 1993) is of particular value in bipolar disorder where symptoms often persist despite treatment. So far, personal recovery has only been studied in researcher-constructed environments (interviews, focus groups). Support forum posts can serve as a complementary naturalistic data source. Objective: The overarching aim of this thesis was to study personal recovery experiences that people living with bipolar disorder have shared in online support forums through integrating health research, NLP, and corpus linguistics in a mixed methods approach within a pragmatic research paradigm, while considering ethical issues and involving people with lived experience. Methods: This mixed-methods study analysed: 1) previous qualitative evidence on personal recovery in bipolar disorder from interviews and focus groups 2) who self-reports a bipolar disorder diagnosis on the online discussion platform Reddit 3) the relationship of mood and posting in mental health-specific Reddit forums (subreddits) 4) discussions of personal recovery in bipolar disorder subreddits. Results: A systematic review of qualitative evidence resulted in the first framework for personal recovery in bipolar disorder, POETIC (Purpose & meaning, Optimism & hope, Empowerment, Tensions, Identity, Connectedness). Mainly young or middle-aged US-based adults self-report a bipolar disorder diagnosis on Reddit. Of these, those experiencing more intense emotions appear to be more likely to post in mental health support subreddits. Their personal recovery-related discussions in bipolar disorder subreddits primarily focussed on three domains: Purpose & meaning (particularly reproductive decisions, work), Connectedness (romantic relationships, social support), Empowerment (self-management, personal responsibility). Support forum data highlighted personal recovery issues that exclusively or more frequently came up online compared to previous evidence from interviews and focus groups. Conclusion: This project is the first to analyse non-reactive data on personal recovery in bipolar disorder. Indicating the key areas that people focus on in personal recovery when posting freely and the language they use provides a helpful starting point for formal and informal carers to understand the concerns of people diagnosed with bipolar disorder and to consider how best to offer support
Processing genome-wide association studies within a repository of heterogeneous genomic datasets
Background
Genome Wide Association Studies (GWAS) are based on the observation of genome-wide sets of genetic variants – typically single-nucleotide polymorphisms (SNPs) – in different individuals that are associated with phenotypic traits. Research efforts have so far been directed to improving GWAS techniques rather than on making the results of GWAS interoperable with other genomic signals; this is currently hindered by the use of heterogeneous formats and uncoordinated experiment descriptions.
Results
To practically facilitate integrative use, we propose to include GWAS datasets within the META-BASE repository, exploiting an integration pipeline previously studied for other genomic datasets that includes several heterogeneous data types in the same format, queryable from the same systems. We represent GWAS SNPs and metadata by means of the Genomic Data Model and include metadata within a relational representation by extending the Genomic Conceptual Model with a dedicated view. To further reduce the gap with the descriptions of other signals in the repository of genomic datasets, we perform a semantic annotation of phenotypic traits. Our pipeline is demonstrated using two important data sources, initially organized according to different data models: the NHGRI-EBI GWAS Catalog and FinnGen (University of Helsinki). The integration effort finally allows us to use these datasets within multisample processing queries that respond to important biological questions. These are then made usable for multi-omic studies together with, e.g., somatic and reference mutation data, genomic annotations, epigenetic signals.
Conclusions
As a result of our work on GWAS datasets, we enable 1) their interoperable use with several other homogenized and processed genomic datasets in the context of the META-BASE repository; 2) their big data processing by means of the GenoMetric Query Language and associated system. Future large-scale tertiary data analysis may extensively benefit from the addition of GWAS results to inform several different downstream analysis workflows
Sex Differences in Epigenetic Signatures of Aging in a Long-Lived Primate
67 pagesAlthough aging impacts everyone, individuals vary in pace and severity of age-related decline. Many long-lived primates, including humans, exhibit marked variation in aging patterns between males and females. We know that environment can influence the aging process, but it remains unknown how the environment shapes aging at the molecular level. The epigenome, responsive to biological and environmental changes, presents a unique opportunity to explore mechanisms that may influence aging. To better understand sex differences in the aging epigenome in the hippocampus and liver, two tissues responsive to age-related change, we characterized differential DNA methylation due to age in unmatched banked hippocampus (N=88; females=57) and liver (N=94; females=58) samples from rhesus macaques across the lifespan. We found the majority of age-associated sites are indeed sex-specific; only 3% of age-associated sites are shared between sexes in the hippocampus and 21% of age-associated sites are shared in the liver. We found that differentially methylated sites (regardless of sex or tissue type) overwhelmingly lose methylation with increasing age, which is consistent with the genomic hypomethylation hypothesis of aging. Ultimately, characterizing sex differences in how the epigenome changes with age across tissues will help identify how environmental factors interact with molecular mechanisms to shape variation in the rate of aging in long-lived primates
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