Description:
Exploring the computational background of ontologies, this self-contained text helps readers understand ontological algorithms and their applications. It describes a host of bio-ontologies, including Gene Ontology and Human Phenotype Ontology. The authors cover graph and inference algorithms and explain how these algorithms are used in biological and biomedical applications. They also offer overviews of the R programming language and the W3C standards of XML, RDF, and OWL. Along with extensive references and many exercises, the book provides software and data on a supporting website.
Review Quotes:
"This book is one of the first source books in the field; it is well written and coherent. Its introduction gives the reader a good taste of what comes next and it also contains good exercises."
--Mohsen Mahmoudi Aznaveh, ACM SIGACT News, 2013
"This welcome book could have been titled 'all you wanted to know about bio-ontologies but didn't dare ask.' In recent years the biological sciences have generated very large, complex data sets whose management, analysis and sharing have created unprecedented challenges. The development of ontologies, originally driven by the invention of the semantic web, has been critical in handling this data and permitting interoperability between databases and between applications. Many of the bio-ontologies and the computational approaches which use them have now become mature, and an understanding of bio-ontologies has really become a requirement for anyone in the mainstream biomedical sciences.
Introduction to Bio-Ontologies provides a self-contained introduction to ontologies for bioinformaticians, computer scientists and biomedical scientists who need to know about the computational background and implementation of ontologies. The book is designed to support either advanced undergraduate or master's courses in bioinformatics or computer science but is also a first stop for any investigator who wants to understand ontologies and how to use them.
The four parts of the book cover basic concepts, specific widely used ontologies, such as the Gene Ontology, algorithms and applications of ontologies. The breadth of coverage is impressive for such a compact volume and there is excellent critical discussion of ontologies from a biological as well as a computational point of view. The book succeeds well in its aim of providing a self-contained primer on ontologies and much of the mathematics used is backed up with detailed explanations and technical appendices which introduce and explain the more co