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dc.contributor.author
Marquart, Kim
dc.contributor.author
Allam, Ahmed
dc.contributor.author
Janjuha, Sharan
dc.contributor.author
Sintsova, Anna
dc.contributor.author
Villiger, Lukas
dc.contributor.author
Frey, Nina
dc.contributor.author
Krauthammer, Michael
dc.contributor.author
Schwank, Gerald
dc.date.accessioned
2021-03-17T12:22:24Z
dc.date.available
2021-01-26T13:35:46Z
dc.date.available
2021-03-17T12:22:24Z
dc.date.issued
2020-07-05
dc.identifier.other
10.1101/2020.07.05.186544
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/465684
dc.description.abstract
Base editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas module and a single-stranded DNA deaminase. They enable conversion of C•G into T•A base pairs and vice versa on genomic DNA. While base editors have vast potential as genome editing tools for basic research and gene therapy, their application has been hampered by a broad variation in editing efficiencies on different genomic loci. Here we perform an extensive analysis of adenine- and cytosine base editors on thousands of lentivirally integrated genetic sequences and establish BE-DICT, an attention-based deep learning algorithm capable of predicting base editing outcomes with high accuracy. BE-DICT is a versatile tool that in principle can be trained on any novel base editor variant, facilitating the application of base editing for research and therapy.
en_US
dc.language.iso
en
en_US
dc.publisher
Cold Spring Harbor Laboratory
en_US
dc.title
Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens
en_US
dc.type
Working Paper
ethz.journal.title
bioRxiv
ethz.size
25 p.
en_US
ethz.publication.place
Cold Spring Harbor, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02030 - Dep. Biologie / Dep. of Biology::02539 - Institut für Molecular Health Sciences / Institute of Molecular Health Sciences::09492 - Schwank, Gerald (ehemalig) / Schwank, Gerald (former)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02030 - Dep. Biologie / Dep. of Biology::02539 - Institut für Molecular Health Sciences / Institute of Molecular Health Sciences::09492 - Schwank, Gerald (ehemalig) / Schwank, Gerald (former)
en_US
ethz.date.deposited
2021-01-26T13:35:54Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-03-17T12:22:36Z
ethz.rosetta.lastUpdated
2023-02-06T21:36:50Z
ethz.rosetta.versionExported
true
ethz.COinS
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