Text Mining on Big and Complex Biomedical Literature

Author:

Xie Boya1,Ding Qin1,Wu Di2

Affiliation:

1. East Carolina University, USA

2. Drexel University, USA

Abstract

Driven by the rapidly advancing techniques and increasing interests in biology and medicine, about 2,000 to 4,000 references are added daily to MEDLINE, the US national biomedical bibliographic database. Even for a specific research topic, extracting useful and comprehensive information out of the huge literature data pool is challenging. Text mining techniques become extremely useful when dealing with the abundant biomedical information and they have been applied to various areas in the realm of biomedical research. Instead of providing a brief overview of all text mining techniques and every major biomedical text mining application, this chapter explores in-depth the microRNA profiling area and related text mining tools. As an illustrative example, one rule-based text mining system developed by the authors is discussed in detail. This chapter also includes the discussion of the challenges and potential research areas in biomedical text mining.

Publisher

IGI Global

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Emerging Trends in Bioinformatics for Breast Cancer Molecular Research;Breast Cancer: Current Trends in Molecular Research;2022-07-14

2. An updated overview and classification of bioinformatics tools for MicroRNA analysis, which one to choose?;Computers in Biology and Medicine;2021-07

3. Colorectal Carcinoma: A General Overview and Future Perspectives in Colorectal Cancer;International Journal of Molecular Sciences;2017-01-19

4. Text Mining;Advances in Data Mining and Database Management;2017

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