By Mihail Popescu, Dong Xu
An ontology is a suite of vocabulary phrases with explicitly acknowledged meanings and kin with different phrases. shortly, progressively more ontologies are being equipped and used for annotating info in biomedical study. because of the super quantity of information being generated, ontologies are actually getting used in different methods, together with connecting various databases, refining seek functions, reading experimental/clinical information, and inferring wisdom. This state-of-the-art source introduces researchers to newest advancements in bio-ontologies. The ebook offers the theoretical foundations and examples of ontologies, in addition to functions of ontologies in biomedicine, from molecular degrees to medical degrees. Readers additionally locate information on technological infrastructure for bio-ontologies. This accomplished, one-stop quantity offers a variety of useful bio-ontology details, supplying execs specified suggestions within the clustering of organic facts, protein type, gene and pathway prediction, and textual content mining.
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Extra resources for Data Mining in Biomedicine Using Ontologies (Artech House Series Bioinformatics & Biomedical Imaging)
6 Types and Examples of Ontologies In this chapter, we have looked at the historical development of ontologies, their components, representations, and engineering. Their uses have been illustrated along the way, but in this section, we will take a longer look at the different types of knowledge artifacts that are referred to as ontologies. Ideally, it would be simple to accurately classify the types of ontologies featured in this section. It can be surprising that in a field that is concerned with the classification of things, that there is no agreed-upon classification of ontologies themselves, even though there are clear differences.
33, Supplement 1, 2005, pp. D334–D337.  Goble, C. , “Transparent Access to Multiple Bioinformatics Information Sources,” IBM Systems J. Special Issue on Deep Computing for the Life Sciences, Vol 40, No. 2, 2001, pp. 532–552. , “A Strategy for Database Interoperation”, J. of Computational Biology, Vol. 2, No. 4, 1995, pp. 573–586. , “Integrating and Exploiting Large-Scale, Heterogeneous, and Autonomous Databases with an Ontology for Molecular Biology,” in Molecular Bioinformatics, Sequence Analysis—The Human Genome Project, R.
2, 2001, pp. 532–552. , “A Strategy for Database Interoperation”, J. of Computational Biology, Vol. 2, No. 4, 1995, pp. 573–586. , “Integrating and Exploiting Large-Scale, Heterogeneous, and Autonomous Databases with an Ontology for Molecular Biology,” in Molecular Bioinformatics, Sequence Analysis—The Human Genome Project, R. Hofestod a. H. ), Aachen, Germany: Shaker Verlag, 1997, pp. 43–56. , “Gene Ontology: Tool for the Unification of Biology,” Nat Genet, Vol. 25, 2000, pp. 25–29. , “The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration,” Nat Biotech, Vol.