The past decade has seen a tremendous growth in the amount of experimental and computa- tional biomedical data, speci cally in the areas of genomics and proteomics. This growth accompanied by an accelerated increase in the number of biomedical publications discussing the ndings. In the last few years, there has been a lot of interest within the scienti c munity in literature-mining tools to help sort through this abundance of literature and the nuggets of information most relevant and useful for speci c analysis tasks. This provides a road map to the various literature-mining methods, both in general and within bioinformatics. It surveys the disciplines involved in unstructured-text analysis, categorizes current work in biomedical literature mining with respect to these disciplines, and provides examples of text analysis methods applied towards meeting some of the current challenges in bioinformatics.
CITATION STYLE
Liebert, M. A. (2003). Genomic Era : An Overview. Journal of Computational Biology, 10(6), 821–855.
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