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Bioinformatics for Diagnosis, Prognosis and Treatment of Complex Diseases pp 57–78Cite as

Biomarker Discovery with Text Mining and Literature Based Discovery

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Part of the book series: Translational Bioinformatics ((TRBIO,volume 4))

Abstract

The huge numbers of biomedical publications provide us valuable data for research. However, how to get usable information from these integrated but unstructured biomedical is a difficult problem in front of us, which calls for biomedical text mining techniques aiming at extracting novel knowledge from scientific texts. In this chapter, we will introduce basis of text mining and examine some frequently used algorithms, tools, and data sets. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in systems biology and each phase of the workflow. Finally, we will discuss the text mining technology for research on biomarkers.

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Notes

  1. 1.

    Pubmed. http://www.ncbi.nlm.nih.gov/pubmed/.

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  1. Center for Systems Biology, Soochow University, No. 1. Shizi Street, Suzhou, P.O. Box 206, 215006, Jiangsu, China

    Fei Zhu & Bairong Shen

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  1. Fei Zhu
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  1. Center for Systems Biology, Soochow University, Suzhou, People's Republic of China

    Bairong Shen

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Zhu, F., Shen, B. (2013). Biomarker Discovery with Text Mining and Literature Based Discovery. In: Shen, B. (eds) Bioinformatics for Diagnosis, Prognosis and Treatment of Complex Diseases. Translational Bioinformatics, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7975-4_4

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