By Mihail Popescu, Dong Xu
An ontology is a suite of vocabulary phrases with explicitly said meanings and kin with different phrases. almost immediately, progressively more ontologies are being outfitted and used for annotating information in biomedical learn. due to the great quantity of knowledge being generated, ontologies are actually getting used in several methods, together with connecting assorted databases, refining seek services, analyzing experimental/clinical info, and inferring wisdom. This state of the art source introduces researchers to newest advancements in bio-ontologies. The e-book offers the theoretical foundations and examples of ontologies, in addition to purposes of ontologies in biomedicine, from molecular degrees to scientific degrees. Readers additionally locate info on technological infrastructure for bio-ontologies. This accomplished, one-stop quantity offers quite a lot of sensible bio-ontology details, supplying execs designated suggestions within the clustering of organic facts, protein category, gene and pathway prediction, and textual content mining.
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Extra resources for Data mining in biomedicine using ontologies
Other psychological research supports asymmetric assessment [6, 22] and justifies the selection of a referent, even when there is not an explicit referent. Different methods have been used to implicitly determine the referent in addition to selecting the object with more salient features . In some cases, there may be a natural reference object or indicator . In others, the degree of an object’s prototypicality  or informativeness  may be used to determine which object serves as the referent.
The assumption is that the ontology is organized in a meaningful and structured way, so that concepts with many descendants communicate less information than leaf concepts. The more descendants a concept has, the less information it expresses. 16) where desc(c) is the number of descendants of concept c, and maxont is the maximum number of concepts in the ontology. 2 A fragment of the WordNet ontology . 17) Note that this is intuitively satisfying since the higher the position of the c3 in the taxonomy, the more abstract c3 is, therefore, the lower the similarity between c1 and c2.
In ontological approaches that determine the similarity between two gene products, first the ontological similarity between all terms annotated to the first gene product and all terms annotated to the second gene product must be determined. Then, in order to produce an overall semantic assessment of the similarity between the two gene products, these term-pair similarities must be aggregated. The resulting overall semantic assessment of gene-product similarity can then be correlated with the sequence similarity between the gene products.