AIMC Topic: Biological Ontologies

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Development of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontology.

SAR and QSAR in environmental research
Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales t...

SORTA: a system for ontology-based re-coding and technical annotation of biomedical phenotype data.

Database : the journal of biological databases and curation
There is an urgent need to standardize the semantics of biomedical data values, such as phenotypes, to enable comparative and integrative analyses. However, it is unlikely that all studies will use the same data collection protocols. As a result, ret...

Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 2.

Journal of integrative bioinformatics
The number, size and complexity of computational models of biological systems are growing at an ever increasing pace. It is imperative to build on existing studies by reusing and adapting existing models and parts thereof. The description of the stru...

The CellML Metadata Framework 2.0 Specification.

Journal of integrative bioinformatics
The CellML Metadata Framework 2.0 is a modular framework that describes how semantic annotations should be made about mathematical models encoded in the CellML (www.cellml.org) format, and their elements. In addition to the Core specification, there ...

MELLO: Medical lifelog ontology for data terms from self-tracking and lifelog devices.

International journal of medical informatics
OBJECTIVE: The increasing use of health self-tracking devices is making the integration of heterogeneous data and shared decision-making more challenging. Computational analysis of lifelog data has been hampered by the lack of semantic and syntactic ...

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

Artificial intelligence in medicine
OBJECTIVE: Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expe...

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

Bioinformatics (Oxford, England)
MOTIVATION: Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task.

Perspectives on next steps in classification of oro-facial pain - part 1: role of ontology.

Journal of oral rehabilitation
The purpose of this study was to review existing principles of oro-facial pain classifications and to specify design recommendations for a new system that would reflect recent insights in biomedical classification systems, terminologies and ontologie...

Combining expert knowledge and knowledge automatically acquired from electronic data sources for continued ontology evaluation and improvement.

Journal of biomedical informatics
INTRODUCTION: A common bottleneck during ontology evaluation is knowledge acquisition from domain experts for gold standard creation. This paper contributes a novel semi-automated method for evaluating the concept coverage and accuracy of biomedical ...

Using ontologies to improve semantic interoperability in health data.

Journal of innovation in health informatics
The present-day health data ecosystem comprises a wide array of complex heterogeneous data sources. A wide range of clinical, health care, social and other clinically relevant information are stored in these data sources. These data exist either as s...