title: Text mining and its potential applications in systems biology.
abstract: With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.
authors.affiliation: School of Computer Science, National Centre for Text Mining, The Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess Street, Manchester M1 7ND, UK. sophia.ananiadou@manchester.ac.uk
authors.forename: Sophia
authors.initials: S
authors.lastname: Ananiadou
authors.forename: Douglas B
authors.initials: DB
authors.lastname: Kell
authors.forename: Jun-ichi
authors.initials: J
authors.lastname: Tsujii
mesh_terms: D001185:Artificial Intelligence; D016247:Information Storage and Retrieval / Q000379:methods*; D008954:Models, Biological; D009323:Natural Language Processing; D011642:Publications; D012107:Research Design; D049490:Systems Biology / Q000379:methods*