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Review
. 2017 Jul 1;58(1):80-89.
doi: 10.1093/ilar/ilx004.

Informatics Support for Basic Research in Biomedicine

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Free PMC article
Review

Informatics Support for Basic Research in Biomedicine

Thomas C Rindflesch et al. ILAR J. .
Free PMC article

Abstract

Informatics methodologies exploit computer-assisted techniques to help biomedical researchers manage large amounts of information. In this paper, we focus on the biomedical research literature (MEDLINE). We first provide an overview of some text mining techniques that offer assistance in research by identifying biomedical entities (e.g., genes, substances, and diseases) and relations between them in text.We then discuss Semantic MEDLINE, an application that integrates PubMed document retrieval, concept and relation identification, and visualization, thus enabling a user to explore concepts and relations from within a set of retrieved citations. Semantic MEDLINE provides a roadmap through content and helps users discern patterns in large numbers of retrieved citations. We illustrate its use with an informatics method we call "discovery browsing," which provides a principled way of navigating through selected aspects of some biomedical research area. The method supports an iterative process that accommodates learning and hypothesis formation in which a user is provided with high level connections before delving into details.As a use case, we examine current developments in basic research on mechanisms of Alzheimer's disease. Out of the nearly 90 000 citations returned by the PubMed query "Alzheimer's disease," discovery browsing led us to 73 citations on sortilin and that disorder. We provide a synopsis of the basic research reported in 15 of these. There is wide-spread consensus among researchers working with a range of animal models and human cells that increased sortilin expression and decreased receptor expression are associated with amyloid beta and/or amyloid precursor protein.

Keywords: Alzheimer’s disease; biomedical informatics; discovery browsing; natural language processing; sortilin; text mining.

Figures

Figure 1.
Figure 1.
Overview of SemRep processing.
Figure 2.
Figure 2.
Overview of Semantic MEDLINE.

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