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Cryopreservation by design : bringing together experiments, simulations and machine learning to deliver the next generation of cryoprotectants
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Warren, Matthew T. (2023) Cryopreservation by design : bringing together experiments, simulations and machine learning to deliver the next generation of cryoprotectants. PhD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b3973270
Item Type: | Thesis (PhD) | ||||
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Subjects: | Q Science > QD Chemistry Q Science > QP Physiology |
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Library of Congress Subject Headings (LCSH): | Cells -- Cryopreservation, Cryopreservation of organs, tissues, etc., Crystallization, Ice crystals -- Growth, Phenylalanine, Antifreeze proteins | ||||
Official Date: | April 2023 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | Warwick Medical School | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Sosso, Gabriele ; Gibson, Matthew I. | ||||
Sponsors: | Medical Research Council (Great Britain) | ||||
Format of File: | |||||
Extent: | xxi, 224 pages : illustrations | ||||
Language: | eng |
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