Ontological knowledge

Laboratory management automation is essential for achieving interoperability in the domain of experimental research and accelerating scientific discovery. The integration of resources and the sharing of knowledge across organisations enable scientific discoveries to be accelerated by increasing the productivity of laboratories, optimising funding efficiency, and addressing emerging global challenges. This paper presents a novel framework for digitalising and automating the administration of research laboratories through The World Avatar, an all-encompassing dynamic knowledge graph...

BACKGROUND: Distinguishing diseases into distinct subtypes is crucial for study and effective treatment strategies. The Open Targets Platform (OT) integrates biomedical, genetic, and biochemical datasets to empower disease ontologies, classifications, and potential gene targets. Nevertheless, many disease annotations are incomplete, requiring laborious expert medical input. This challenge is especially pronounced for rare and orphan diseases, where resources are scarce. METHODS: We present a machine learning approach to identifying diseases with potential subtypes, using the approximately 23,000 diseases documented in OT...

MOTIVATION: Whole-exome and genome sequencing have become common tools in diagnosing patients with rare diseases. Despite their success, this approach leaves many patients undiagnosed. A common argument is that more disease variants still await discovery, or the novelty of disease phenotypes results from a combination of variants in multiple disease-related genes. Interpreting the phenotypic consequences of genomic variants relies on information about gene functions, gene expression, physiology, and other genomic features...

Adverse Outcome Pathways (AOPs) have been proposed to facilitate mechanistic understanding of interactions of chemicals/materials with biological systems. Each AOP starts with a molecular initiating event (MIE) and possibly ends with adverse outcome(s) (AOs) via a series of key events (KEs). So far, the interaction of engineered nanomaterials (ENMs) with biomolecules, biomembranes, cells, and biological structures, in general, is not yet fully elucidated. There is also a huge lack of information on which AOPs are ENMs-relevant or -specific, despite numerous published data on toxicological endpoints they trigger, such as oxidative stress and inflammation...

Pyrus (pear) is among the most nutritious fruits and contains fibers that have great health benefits to humans. It is mostly cultivated in temperate regions globally and is highly subjected to biotic and abiotic stresses which affect its yield. Pheophorbide a oxygenase (PAO) is an essential component of the chlorophyll degradation system and contributes to the senescence of leaves. It is responsible for opening the pheophorbide a porphyrin macrocycle and forming the main fluorescent chlorophyll catabolite However, this gene family and its members have not been explored in Pyrus genomes...

This study applies Semantic Web technologies to advance Materials Science and Engineering (MSE) through the integration of diverse datasets. Focusing on a 2000 series age-hardenable aluminum alloy, we correlate mechanical and microstructural properties derived from tensile tests and dark-field transmission electron microscopy across varied aging times. An expandable knowledge graph, constructed using the Tensile Test and Precipitate Geometry Ontologies aligned with the PMD Core Ontology, facilitates this integration...

Goats have achieved global prominence as essential livestock since their initial domestication, primarily owing to their remarkable adaptability to diverse environmental and production systems. Differential selection pressures influenced by climate have led to variations in their physical attributes, leaving genetic imprints within the genomes of goat breeds raised in diverse agroecological settings. In light of this, our study pursued a comprehensive analysis, merging environmental data with single nucleotide polymorphism (SNP) variations, to unearth indications of selection shaped by climate-mediated forces in goats...

The N6 -methyladenosine reader YTH N6 -methyladenosine RNA binding protein 1 (YTHDF1) has been assessed in several tumor types and holds significance in the tumor microenvironment (TME). Furthermore, p53, an important tumor suppressor, is closely associated with the TME. The present study evaluated the roles of YTHDF1 and p53 in regulating the TME in gastric cancer (GC). Genetic alterations in the YTH domain family were analyzed using the cBioPortal database. Expression of YTHDF1 in GC cells and tissues was assessed using the Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham Cancer data analysis portal and Tumor-Immune System Interactions and Drug Bank (TISIDB) databases, along with reverse-transcription-quantitative PCR and western blotting in GC...

BACKGROUND: Through pressure from funding and governing bodies, an audit culture invades the rhetoric of the dance medicine and science research community, leading to undue focus on justifying and legitimizing the holistic benefits of dancing. This paper critiques this hierarchical value system which disproportionately favors objective, generalizable, and quantitative research approaches still dominant in dance medicine and science, existing since the founding of the International Association for Dance Medicine and Science (IADMS) in 1990...

In the highly competitive field of material manufacturing, stakeholders strive for the increased quality of the end products, reduced cost of operation, and the timely completion of their business processes. Digital twin (DT) technologies are considered major enablers that can be deployed to assist the development and effective provision of manufacturing processes. Additionally, knowledge graphs (KG) have emerged as efficient tools in the industrial domain and are able to efficiently represent data from various disciplines in a structured manner while also supporting advanced analytics...

Diabetes management requires constant monitoring and individualized adjustments. This study proposes a novel approach that leverages digital twins and personal health knowledge graphs (PHKGs) to revolutionize diabetes care. Our key contribution lies in developing a real-time, patient-centric digital twin framework built on PHKGs. This framework integrates data from diverse sources, adhering to HL7 standards and enabling seamless information access and exchange while ensuring high levels of accuracy in data representation and health insights...

Proteins need to be located in appropriate spatiotemporal contexts to carry out their diverse biological functions. Mislocalized proteins may lead to a broad range of diseases, such as cancer and Alzheimer's disease. Knowing where a target protein resides within a cell will give insights into tailored drug design for a disease. As the gold validation standard, the conventional wet lab uses fluorescent microscopy imaging, immunoelectron microscopy, and fluorescent biomarker tags for protein subcellular location identification...

In recent years, with the trend of open science, there have been many efforts to share research data on the internet. To promote research data sharing, data curation is essential to make the data interpretable and reusable. In research fields such as life sciences, earth sciences, and social sciences, tasks and procedures have been already developed to implement efficient data curation to meet the needs and customs of individual research fields. However, not only data sharing within research fields but also interdisciplinary data sharing is required to promote open science...

Ontologies serve as comprehensive frameworks for organizing domain-specific knowledge, offering significant benefits for managing clinical data. This study presents the development of the Fall Risk Management Ontology (FRMO), designed to enhance clinical text mining, facilitate integration and interoperability between disparate data sources, and streamline clinical data analysis. By representing major entities within the fall risk management domain, the FRMO supports the unification of clinical language and decision-making processes, ultimately contributing to the prevention of falls among older adults...

Course-based undergraduate research experiences (CUREs) can reduce barriers to research opportunities while increasing student knowledge and confidence. However, the number of widely adopted, easily transferable CUREs is relatively small. Here, we describe a CURE aimed at determining the function of poorly characterized Saccharomyces cerevisiae genes. More than 20 years after sequencing of the yeast genome, nearly 10% of open reading frames (ORFs) still have at least one uncharacterized Gene Ontology (GO) term...

Recent developments in cardiac macrophage biology have broadened our understanding of the critical functions of macrophages in the heart. As a result, there is further interest in understanding the independent contributions of distinct subsets of macrophage to cardiac development and function. Here, we demonstrate that genetic loss of interferon regulatory factor 8 (Irf8)-positive embryonic-derived macrophages significantly disrupts cardiac conduction, chamber function, and innervation in adult zebrafish. At 4 months post-fertilization (mpf), homozygous irf8st96/st96 mutants have significantly shortened atrial action potential duration and significant differential expression of genes involved in cardiac contraction...

In this paper, we focus on indexing mechanisms for unstructured clinical big integrated data repository systems. Clinical data is unstructured and heterogeneous, which comes in different files and formats. Accessing data efficiently and effectively are critical challenges. Traditional indexing mechanisms are difficult to apply on unstructured data, especially by identifying correlation information between clinical data elements. In this research work, we developed a correlation-aware relevance-based index that retrieves clinical data by fetching most relevant cases efficiently...

BACKGROUND OBJECTIVES: Mosquito vectors are disease-causing insects, responsible for various life-threatening vector-borne diseases such as dengue, Zika, malaria, chikungunya, and lymphatic filariasis. In practice, synthetic insecticides are used to control the mosquito vector, but, the continuous usage of synthetic insecticides is toxic to human health resulting in communicable diseases. Non-toxic biocontrol agents such as bacteria, fungus, plants, and mosquito densoviruses play a vital role in controlling mosquitoes...

Transformer neural networks show promising capabilities, in particular for uses in materials analysis, design, and manufacturing, including their capacity to work effectively with human language, symbols, code, and numerical data. Here, we explore the use of large language models (LLMs) as a tool that can support engineering analysis of materials, applied to retrieving key information about subject areas, developing research hypotheses, discovery of mechanistic relationships across disparate areas of knowledge, and writing and executing simulation codes for active knowledge generation based on physical ground truths...

Functional annotation based on Gene Ontology has provided a structured and comprehensive system to access the current knowledge about the function of genes. For model plants such as Arabidopsis thaliana , there is a constant updating and restructuring of the functional annotation that increases the reliability of the analyses that use it. For tomato ( Solanum lycopersicum ), a crop widely used as a model plant for the study of fleshy fruits, there is no functional annotation, at least not freely accessible, even though its genome has long been sequenced and annotated...