Ontology Engineering in Life Sciences
Life sciences is flourishing with ontologies that biologists use to make sense of their experiments. For inferring correct conclusions from experiments, ontologies have to be structured optimally against the knowledge base they represent. The structure of an ontology needs to be changed continuously so that it is an accurate representation of the underlying domain.
Recently, an automated method was introduced for engineering ontologies in life sciences such as Gene Ontology (GO), one of the most successful and widely used biomedical ontology. Based on information theory, it restructures ontologies so that the levels represent the desired specificity of the concepts. Similar information theoretic approaches have also been used for optimal partition of Gene Ontology. Given the mathematical nature of such engineering algorithms, these optimizations can be automated to produce a principled and scalable architecture to restructure ontologies such as GO.
Open Biomedical Ontologies (OBO), a 2006 initiative of the U.S. National Center for Biomedical Ontology, that provides a common 'foundry' for various ontology initiatives, amongst which are:
- The Generic Model Organism Project (GMOD)
- Gene Ontology Consortium
- Sequence Ontology
- Ontology Lookup Service
- The Plant Ontology Consortium
- Standards and Ontologies for Functional Genomics
and more
Read more about this topic: Ontology Engineering
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