TY - JOUR AU - Breimyer, Paul AU - Green, Nathan AU - Kumar, Vinay AU - Samatova, Nagiza F. PY - 2009 DA - 2009/11/03 TI - BioDEAL: community generation of biological annotations JO - BMC Medical Informatics and Decision Making SP - S5 VL - 9 IS - 1 AB - Publication databases in biomedicine (e.g., PubMed, MEDLINE) are growing rapidly in size every year, as are public databases of experimental biological data and annotations derived from the data. Publications often contain evidence that confirm or disprove annotations, such as putative protein functions, however, it is increasingly difficult for biologists to identify and process published evidence due to the volume of papers and the lack of a systematic approach to associate published evidence with experimental data and annotations. Natural Language Processing (NLP) tools can help address the growing divide by providing automatic high-throughput detection of simple terms in publication text. However, NLP tools are not mature enough to identify complex terms, relationships, or events. SN - 1472-6947 UR - https://doi.org/10.1186/1472-6947-9-S1-S5 DO - 10.1186/1472-6947-9-S1-S5 ID - Breimyer2009 ER -