Kirjailija
Dong Xu
Kirjat ja teokset yhdessä paikassa: 4 kirjaa, julkaisuja vuosilta 2008–2011, suosituimpiin kuuluu Data Mining Applications Using Ontologies in Biomedicine. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.
4 kirjaa
Kirjojen julkaisuvuodet: 2008–2011.
Data Mining Applications Using Ontologies in Biomedicine
Mihail Popescu; Dong Xu
Artech House
2009
sidottu
An ontology is a set of vocabulary terms with explicitly stated meanings and relations with other terms. Presently, a growing number of ontologies are being built and used for annotating data in biomedical research. Thanks to the tremendous amount of data being generated, ontologies are now being used in numerous ways, including connecting different databases, refining search capabilities, interpreting experimental/clinical data, and inferring knowledge. This cutting-edge resource introduces researchers to latest developments in bio-ontologies. The book provides the theoretical foundations and examples of ontologies, as well as applications of ontologies in biomedicine, from molecular levels to clinical levels. Readers also find details on technological infrastructure for bio-ontologies. This comprehensive, one-stop volume presents a wide range of practical bio-ontology information, offering professionals detailed guidance in the clustering of biological data, protein classification, gene and pathway prediction, and text mining.
Applications Of Fuzzy Logic In Bioinformatics
Dong Xu; James M Keller; Rajkumar Bondugula; Mihail Popescu
Imperial College Press
2008
sidottu
Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. In addition, it has been shown that exact or optimal methods have significant limitation in many bioinformatics problems. Fuzzy set theory and fuzzy logic are ideal to describe some biological systems/objects and provide good tools for some bioinformatics problems. This book comprehensively addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and microarray data analysis. It also reviews other bioinformatics applications using fuzzy techniques.