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Mining Emerging Biomedical Literature for Understanding Disease Associations in Drug Discovery

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Biomedical Literature Mining

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1159))

Abstract

Systematically evaluating the exponentially growing body of scientific literature has become a critical task that every drug discovery organization must engage in in order to understand emerging trends for scientific investment and strategy development. Developing trends analysis uses the number of publications within a 3-year window to determine concepts derived from well-established disease and gene ontologies to aid in recognizing and predicting emerging areas of scientific discoveries relevant to that space. In this chapter, we describe such a method and use obesity and psoriasis as use-case examples by analyzing the frequency of disease-related MeSH terms in PubMed abstracts over time. We share how our system can be used to predict emerging trends at a relatively early stage and we analyze the literature-identified genes for genetic associations, druggability, and biological pathways to explore any potential biological connections between the two diseases that could be utilized for drug discovery.

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Authors and Affiliations

  1. Computational Biology, GlaxoSmithKline R&D, Research Triangle Park, North Carolina, NC, USA

    Deepak K. Rajpal, Xiaoyan A. Qu & Johannes M. Freudenberg

  2. Computational Biology, GlaxoSmithKline R&D, King of Prussia, PA, USA

    Vinod D. Kumar

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  1. Deepak K. Rajpal
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  2. Xiaoyan A. Qu
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  3. Johannes M. Freudenberg
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  4. Vinod D. Kumar
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Correspondence to Vinod D. Kumar .

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Editors and Affiliations

  1. GlaxoSmithKline, King of Prussia, Pennsylvania, USA

    Vinod D. Kumar

  2. GlaxoSmithKline, Hitchin, Hertfordshire, United Kingdom

    Hannah Jane Tipney

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Rajpal, D.K., Qu, X.A., Freudenberg, J.M., Kumar, V.D. (2014). Mining Emerging Biomedical Literature for Understanding Disease Associations in Drug Discovery. In: Kumar, V., Tipney, H. (eds) Biomedical Literature Mining. Methods in Molecular Biology, vol 1159. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0709-0_11

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  • DOI: https://doi.org/10.1007/978-1-4939-0709-0_11

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