Learn More
UNLABELLED We present a biomedical text-mining system focused on four types of gene-related information: biological functions, associated diseases, related genes and gene-gene relations. The aim of this system is to provide researchers an easy-to-use bio-information service that will rapidly survey the rapidly burgeoning biomedical literature. (More)
MOTIVATION Research on roles of gene products in cells is accumulating and changing rapidly, but most of the results are still reported in text form and are not directly accessible by computers. To expedite the progress of functional bioinformatics, it is, therefore, important to efficiently process large amounts of biomedical literature and transform the(More)
In this report, we present the system that we built for task 2 of the BioCreAtIvE competition, which is based on the MeKE (Medical Knowledge Explorer) system [3] developed earlier. Our system combines the high-precis ion advantage of a pattern matching approach and the little-human-effort advantage of a sentence classification approach, and creates great(More)
With the rapid growth of articles of genomics research, it has become a challenge for biomedical researchers to access this ever-increasing quantity of information to understand the newest discovery of functions of proteins they are studying. To facilitate functional annotation of proteins by utilizing the huge amounts of biomedical literature and(More)
  • 1