An Exploration of Mining Gene Expression Mentions and their Anatomical Locations from Biomedical Text

Here we explore mining data on gene expres-sion from the biomedical literature and present Gene Expression Text Miner (GETM), a tool for extraction of information about the expression of genes and their ana-tomical locations from text. Provided with recognized gene mentions, GETM identifies mentions of anatomical locations and cell lines, and extracts text passages where au-thors discuss the expression of a particular gene in specific anatomical locations or cell lines. This enables the automatic construction of expression profiles for both genes and ana-tomical locations. Evaluated against a ma-nually extended version of the BioNLP '09 corpus, GETM achieved precision and recall levels of 58.8% and 23.8%, respectively. Ap-plication of GETM to MEDLINE and PubMed Central yielded over 700,000 gene expression mentions. This data set may be queried through a web interface, and should prove useful not only for researchers who are interested in the developmental regulation of specific genes of interest, but also for data-base curators aiming to create structured re-positories of gene expression information. The compiled tool, its source code, the ma-nually annotated evaluation corpus and a search query interface to the data set ex-tracted from MEDLINE and PubMed Cen-tral is available at http://getm-project.sourceforge.net/.