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Data mining a medieval medical text reveals patterns in ingredient choice that reflect biological activity against infectious agents
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Connelly, Erin, Del Genio, Charo I., Harrison, Freya and Nacy, Carol A. (2020) Data mining a medieval medical text reveals patterns in ingredient choice that reflect biological activity against infectious agents. mBio, 11 (1). e03136-19. doi:10.1128/mBio.03136-19 ISSN 2150-7511.
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WRAP-data-mining-medieval-medical-text-patterns-biological-agents-Harrison-2020.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (955Kb) | Preview |
Official URL: http://dx.doi.org/10.1128/mBio.03136-19
Abstract
The pharmacopeia used by physicians and laypeople in medieval Europe has largely been dismissed as placebo or superstition. While we now recognize that some of the materia medica used by medieval physicians could have had useful biological properties, research in this area is limited by the labor-intensive process of searching and interpreting historical medical texts. Here, we demonstrate the potential power of turning medieval medical texts into contextualized electronic databases amenable to exploration by the use of an algorithm. We used established methodologies from network science to reveal patterns in ingredient selection and usage in a key text, the 15th-century Lylye of Medicynes, focusing on remedies to treat symptoms of microbial infection. 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.
| Item Type: | Journal Article | ||||||||||||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QR Microbiology R Medicine > R Medicine (General) R Medicine > RM Therapeutics. Pharmacology |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | ||||||||||||||||||
| Library of Congress Subject Headings (LCSH): | Drug resistance in microorganisms, Antibiotics, Anti-infective agents, Data mining, Medicine, Medieval | ||||||||||||||||||
| Journal or Publication Title: | mBio | ||||||||||||||||||
| Publisher: | American Society for Microbiology | ||||||||||||||||||
| ISSN: | 2150-7511 | ||||||||||||||||||
| Official Date: | 11 February 2020 | ||||||||||||||||||
| Dates: |
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| Volume: | 11 | ||||||||||||||||||
| Number: | 1 | ||||||||||||||||||
| Article Number: | e03136-19 | ||||||||||||||||||
| DOI: | 10.1128/mBio.03136-19 | ||||||||||||||||||
| Status: | Peer Reviewed | ||||||||||||||||||
| Publication Status: | Published | ||||||||||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||||||||
| Date of first compliant deposit: | 12 February 2020 | ||||||||||||||||||
| Date of first compliant Open Access: | 25 February 2020 | ||||||||||||||||||
| RIOXX Funder/Project Grant: |
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