The bibliome of biomedical literature is already too large and growing much too rapidly for researchers to stay current on all information relevant to their work. Text mining and knowledge extraction can assist researchers by analyzing bibliographic databases as a whole and extracting knowledge by connecting information between multiple records. Symbolic network logistical analysis -- a novel text mining method based on analyzing the network structure created by symbol occurrences -- was developed as a way to extend the capabilities of knowledge extraction.