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Datamining a medieval medical text reveals patterns in ingredient choice that reflect biological activity against the causative agents of specified infections

Erin Connelly, Charo I. del Genio, Freya Harrison
doi: https://doi.org/10.1101/368779
Erin Connelly
1Schoenberg Institute for Manuscript Studies, University of Pennsylvania, Philadelphia, PA 19010
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  • For correspondence: erincon@upenn.edu
Charo I. del Genio
2School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
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  • For correspondence: c.i.del-genio@warwick.ac.uk
Freya Harrison
3School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
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  • For correspondence: f.harrison@warwick.ac.uk
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Abstract

The pharmacopeia used by physicians and lay people in medieval Europe has largely been dismissed as placebo or superstition. While we now recognise that some of the materia medica used by medieval physicians could have had useful biological properties, research in this area is limited by the labour-intensive process of searching and interpreting historical medical texts. Here, we demonstrate the potential power of turning medieval medical texts into contextualised electronic databases amenable to exploration by algorithm. We use established methodologies from network science to reveal statistically significant patterns in ingredient selection and usage in a key text, the fifteenth-century Lylye of Medicynes, focusing on remedies to treat symptoms of microbial infection. We discuss the potential that these patterns reflect rational medical decisions. In providing a worked example of data-driven textual analysis, we demonstrate the potential of this approach to encourage interdisciplinary collaboration and to shine a new light on the ethnopharmacology of historical medical texts.

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Posted July 16, 2018.
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Datamining a medieval medical text reveals patterns in ingredient choice that reflect biological activity against the causative agents of specified infections
Erin Connelly, Charo I. del Genio, Freya Harrison
bioRxiv 368779; doi: https://doi.org/10.1101/368779
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Datamining a medieval medical text reveals patterns in ingredient choice that reflect biological activity against the causative agents of specified infections
Erin Connelly, Charo I. del Genio, Freya Harrison
bioRxiv 368779; doi: https://doi.org/10.1101/368779

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