Discovering biomedical knowledge from the literature.

Abstract

Biomedical knowledge is to a very large extent represented only in textual form. To make this knowledge accessible to humans and/or further automatic processing, text mining applications have been developed. At the end of this chapter we present an overview of the most important open access applications and their functionality. The main part of the paper is devoted to the major problems with which all such applications have to deal. The first problem is terminology processing, i.e., recognizing biomedical terms and identifying their meanings, at least to a certain degree. The second problem is to bring together information units that are distributed over more than one sentence. The task of coreference resolution consists of identifying the entities to which the text refers in different sentences and in different ways. The third problem we discuss is that of information extraction, in particular, extraction of relational information. The representation of the domain knowledge is an indispensable component of any text mining application. We discuss different types and depths of ontological modeling and how this knowledge helps to accomplish the tasks described above. An overview of ontological resources is given at the end of the chapter.

DOI: 10.1007/978-1-59745-398-1_26

Cite this paper

@article{Saric2008DiscoveringBK, title={Discovering biomedical knowledge from the literature.}, author={Jasmin Saric and Henriette Engelken and Uwe Reyle}, journal={Methods in molecular biology}, year={2008}, volume={484}, pages={415-33} }