Text analytics for life science using the Unstructured Information Management Architecture

TLDR

Biomedical text is essential for knowledge discovery in life science, supporting both basic bioinformatics research and industry sectors such as medical informatics, clinical genomics, and drug development. The paper describes the value of text analysis in biomedical research, the development of the BioTeKS system, and its applications. The authors built BioTeKS, a prototype system based on IBM Research’s UIMA framework that automatically extracts biomedical entities and related concepts from MEDLINE abstracts, medical records, and patents to enable text analysis, search, and mining.

Abstract

Biomedical text plays a fundamental role in knowledge discovery in life science, in both basic research (in the field of bioinformatics) and in industry sectors devoted to improving medical practice, drug development, and health care (such as medical informatics, clinical genomics, and other sectors). Several groups in the IBM Research Division are collaborating on the development of a prototype system for text analysis, search, and text-mining methods to support problem solving in life science. The system is called "BioTeKS" ("Biological Text Knowledge Services"), and it integrates research technologies from multiple IBM Research labs. BioTeKS is also the first major application of the UIMA (Unstructured Information Management Architecture) initiative also emerging from IBM Research. BioTeKS is intended to analyze biomedical text such as MEDLINE™ abstracts, medical records, and patents; text is analyzed by automatically identifying terms or names corresponding to key biomedical entities (e.g., "genes," "proteins," "compounds," or "drugs") and concepts or facts related to them. In this paper, we describe the value of text analysis in biomedical research, the development of the BioTeKS system, and applications which demonstrate its functions.