AIMC Topic: Biological Ontologies

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Design of the formalized and integrated Alzheimer's Disease Ontology and its application in retrieving textual data via text mining.

Database : the journal of biological databases and curation
As one of the leading causes for dementia in the population, it is imperative that we discern exactly why Alzheimer's disease (AD) has a strong molecular association with beta-amyloid and tau. Although a clear understanding about etiology and pathoge...

Phen2Disease: a phenotype-driven model for disease and gene prioritization by bidirectional maximum matching semantic similarities.

Briefings in bioinformatics
Human Phenotype Ontology (HPO)-based approaches have gained popularity in recent times as a tool for genomic diagnostics of rare diseases. However, these approaches do not make full use of the available information on disease and patient phenotypes. ...

SBOannotator: a Python tool for the automated assignment of systems biology ontology terms.

Bioinformatics (Oxford, England)
MOTIVATION: The number and size of computational models in biology have drastically increased over the past years and continue to grow. Modeled networks are becoming more complex, and reconstructing them from the beginning in an exchangeable and repr...

KG-Hub-building and exchanging biological knowledge graphs.

Bioinformatics (Oxford, England)
MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is...

K-RET: knowledgeable biomedical relation extraction system.

Bioinformatics (Oxford, England)
MOTIVATION: Relation extraction (RE) is a crucial process to deal with the amount of text published daily, e.g. to find missing associations in a database. RE is a text mining task for which the state-of-the-art approaches use bidirectional encoders,...

Using language models and ontology topology to perform semantic mapping of traits between biomedical datasets.

Bioinformatics (Oxford, England)
MOTIVATION: Human traits are typically represented in both the biomedical literature and large population studies as descriptive text strings. Whilst a number of ontologies exist, none of these perfectly represent the entire human phenome and exposom...

Ontologies in the New Computational Age of Radiology: RadLex for Semantics and Interoperability in Imaging Workflows.

Radiographics : a review publication of the Radiological Society of North America, Inc
From basic research to the bedside, precise terminology is key to advancing medicine and ensuring optimal and appropriate patient care. However, the wide spectrum of diseases and their manifestations superimposed on medical team-specific and discipli...

A knowledge-based decision support system for inferring supportive treatment recommendations for diabetes mellitus.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Diabetes Mellitus (DM) is a significant risk, mostly causing blindness, kidney failure, heart attack, stroke, and lower limb amputation. A Clinical Decision Support System (CDSS) can assist healthcare practitioners in their daily effort a...

mOWL: Python library for machine learning with biomedical ontologies.

Bioinformatics (Oxford, England)
MOTIVATION: Ontologies contain formal and structured information about a domain and are widely used in bioinformatics for annotation and integration of data. Several methods use ontologies to provide background knowledge in machine learning tasks, wh...

CTS2 OWL: Mapping OWL Ontologies to CTS2 Terminology Resources.

Studies in health technology and informatics
The advancement of healthcare towards P5 medicine requires communication and cooperation between all actors and institutions involved. Interoperability must go beyond integrating data from different sources and include the understanding of the meanin...