Introduction to Bio-Ontologies explores the computational background of ontologies. Emphasizing computational and algorithmic issues surrounding bio-ontologies, this self-contained text helps readers understand ontological algorithms and their applications.The first part of the book defines ontology and bio-ontologies. It also explains the importan

Peter N. Robinson is a research scientist and leader of the Computational Biology Group in the Institute of Medical Genetics and Human Genetics at Charite-Universitätmedizin Berlin. Dr. Robinson completed his medical education at the University of Pennsylvania, followed by an internship at Yale University. He also studied mathematics and computer science at Columbia University. His research interests involve the use of mathematical and bioinformatics models to understand biology and hereditary disease.

Sebastian Bauer is a research assistant in the Institute of Medical Genetics and Human Genetics at Charite-Universitätmedizin Berlin. He earned a degree in computer science from the Technical University of Ilmenau. His research interests include mathematical modeling, discrete algorithms, theoretical computer science, software engineering, and the applications of these fields to medicine and biology.

Basic Concepts: Ontologies and Applications of Ontologies in Biomedicine. Mathematical Logic and Inference. Probability Theory and Statistics for Bio-Ontologies. Ontology Languages. Bio-Ontologies: The Gene Ontology. Upper-Level Ontologies. A Selective Survey of Bio-Ontologies. Graph Algorithms for Bio-Ontologies: Overrepresentation Analysis. Model-Based Approaches to GO Analysis. Semantic Similarity. Frequency-Aware Bayesian Network Searches in Attribute Ontologies. Inference in Ontologies: Inference in the Gene Ontology. RDFS Semantics and Inference. Inference in OWL Ontologies. Algorithmic Foundations of Computational Inference. SPARQL. Appendices. Bibliography. Index.