document: Knowledge modeling and its application in life sciences : a tale of two ontologies High throughput glycoproteomics , similar to genomics and proteomics , involves extremely large volumes of distributed , heterogeneous data as a basis for identification and quantification of a structurally diverse collection of biomolecules . The ability to share , compare , query for and most critically correlate datasets using the native biological relationships are some of the challenges being faced by glycobiology researchers . As a solution for these challenges , we are building a semantic structure , using a suite of ontologies , which supports management of data and information at each step of the experimental lifecycle . This framework will enable researchers to leverage the large scale of glycoproteomics data to their benefit . In this paper , we focus on the design of these biological ontology schemas with an emphasis on relationships between biological concepts , on the use of novel approaches to populate these complex ontologies including integrating extremely large datasets ( 500MB ) as part of the instance base and on the evaluation of ontologies using OntoQA ( 38 ) metrics . The application of these ontologies in providing informatics solutions , for high throughput glycoproteomics experimental domain , is also discussed . We present our experience as a use case of developing two ontologies in one domain , to be part of a set of use cases , which are used in the development of an emergent framework for building and deploying biological ontologies .
doc_bio_tags: O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O