Text analytics for life science using the unstructured information management architecture

被引:27
作者
Mack, R
Mukherjea, S
Soffer, A
Uramoto, N
Brown, E
Coden, A
Cooper, J
Inokuchi, A
Iyer, B
Mass, Y
Matsuzawa, H
Subramaniam, LV
机构
[1] IBM Corp, Thomas J Watson Res Ctr, Div Res, Hawthorne, NY 10532 USA
[2] IBM Corp, Div Res, India Res Lab, New Delhi 110017, India
[3] IBM Corp, Div Res, Haifa Res Lab, IL-31905 Haifa, Israel
[4] IBM Corp, Div Res, Tokyo Res Lab, Yamato, Kanagawa, Japan
关键词
D O I
10.1147/sj.433.0490
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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(TM) 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.
引用
收藏
页码:490 / 515
页数:26
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