Integrating phenotype ontologies across multiple species

Integrating phenotype ontologies with PhenomeNET

BACKGROUND Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomical details being captured in clinical and model organism databases presents complex problems when attempting to match classes across species and across phenotypes as diverse as b...

Ontologies improve cross-species phenotype analysis

As phenotype data analysis has become an important component of functional genomics, many methods for analyzing these data have been published in the recent past. For example, RNA interference (RNAi) in mice has significantly improved our understanding of gene regulation, even for human disease. However, as phenotypes are obtained through species-specific experiments, they are usually described...

Integrating Anatomy and Phenotype Ontologies with Taxonomic Hierarchies

Reasoning about Models across Multiple Ontologies

One of the central issues of intelligent CAD is building a modeling mechanism that deals with various models . The world in which a model is built, which call ontology, may vary over domains of modeling, abstraction levels . and granularities . This paper discusses integration of design object models over multiple ontologies . The key idea is the use of meta-level model about relationships amon...

Integrating metabolomics profiling measurements across multiple biobanks.

To optimize the quality of large scale mass-spectrometry based metabolomics data obtained from semiquantitative profiling measurements, it is important to use a strategy in which dedicated measurement designs are combined with a strict statistical quality control regime. This assures consistently high-quality results across measurements from individual studies, but semiquantitative data have be...