Systems biology is an emerging multi-disciplinary field in which the behaviour of complex biological systems is studied by considering the interaction of all cellular and molecular constituents rather than using a "traditional" reductionist approach where constituents are studied individually. Systems are often studied over time with the ultimate goal of developing models which can be used to predict and understand complex biological processes, such as human diseases. To support systems biology, a large number of biological pathways are being derived for many different organisms, and these are stored in various databases. There is a lack of and need for algorithms for analysis of biological pathways. Here, a thesis is proposed where three related methods are developed for semantic analysis of biological pathways utilising the Gene Ontology. It is believed that the methods will be useful to biologists in order to assess the biological plausibility of derived pathways, compare different pathways for semantic similarities, and to derive hypothetical pathways that are semantically similar to documented biological pathways. To our knowledge, all methods are novel, and will therefore extend the bioinformatics toolbox that biologists can use to make new biological discoveries.