Mining literature for systems biology

Abstract

Currently, literature is integrated in systems biology studies in three ways. Hand-curated pathways have been sufficient for assembling models in numerous studies. Second, literature is frequently accessed in a derived form, such as the concepts represented by the Medical Subject Headings (MeSH) and Gene Ontologies (GO), or functional relationships captured in protein-protein interaction (PPI) databases; both of these are convenient, consistent reductions of more complex concepts expressed as free text in the literature. Moreover, their contents are easily integrated into computational processes required for dealing with large data sets. Last, mining text directly for specific types of information is on the rise as text analytics methods become more accurate and accessible. These uses of literature, specifically manual curation, derived concepts captured in ontologies and databases, and indirect and direct application of text mining, will be discussed as they pertain to systems biology.