This thesis discusses potential applications of semantics to the recent literaturebased informatics systems to facilitate knowledge discovery, hypothesis generation, and literature retrieval in the domain of biomedicine. The approaches presented herein make use of semantic information extracted from biomedical texts by natural language processing systems supported by biomedical ontologies. The thesis is divided into two main parts: First, a field of literature-based discovery is introduced, with a review of recent approaches of the field; second, literature retrieval in the domain of neuroimaging (neuroscience) is discussed with the emphasis put on the coordinate-based searching of related publications. My own contribution to the first part is a novel literature-based `discovery browsing' methodology incorporating semantic predications, graph theory and path analysis for guiding researchers through the relevant literature on a user-specied biomedical phenomenon. Moreover, the additional analyses of the methodology show its potential application as a support for the recent probabilistic retrieval methods. In the second part of the thesis, I present the BredeQuery plugin which integrates a coordinate-based literature retrieval system with the common in neuroimaging statistical analysis environment. It is followed by the detailed description of a prototype of context-dependent neuroscientic literature retrieval methodology, which thanks to the employment of ontologies, allows the user to define context of interest for a search. The peer reviewed research articles, included in the appendices, discuss further the details of the presented methods, case studies, and provide other related information.