Thesis
Structure-aware and interpretable machine learning for CRISPR-Cas9 cleavage activity prediction
- Abstract:
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The approval of the ex vivo CRISPR-based gene therapy Casgevy in 2023 shows the potential of CRISPR-based cures for genetic diseases. However, off-target effects induced by heteroduplex mismatches tolerated by Cas9 nucleases limit clinical adoption of the genome editing technology. Despite the advances in developing accurate CRISPR-Cas9 cleavage activity tools and determining factors influencing Cas9 cleavage activity, most tools remain confined to features relating to the spacer-target inter...
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- Files:
-
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(Preview, Dissemination version, pdf, 17.5MB, Terms of use)
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Authors
Contributors
+ Minary, P
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Computer Science
- Role:
- Supervisor
- ORCID:
- 0000-0002-1779-6741
- DOI:
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
- Language:
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English
- Keywords:
- Subjects:
- Deposit date:
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2026-06-18
- ARK identifier:
Terms of use
- Copyright holder:
- Jeffrey Kelvin Mak
- Copyright date:
- 2025
- Licence:
- CC Attribution (CC BY)
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