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Lenti_gRNA-Puro Citations (13)

Originally described in: In vivo high-throughput profiling of CRISPR-Cpf1 activity.
Kim HK, Song M, Lee J, Menon AV, Jung S, Kang YM, Choi JW, Woo E, Koh HC, Nam JW, Kim H Nat Methods. 2016 Dec 19. doi: 10.1038/nmeth.4104. PubMed Journal

Articles Citing Lenti_gRNA-Puro

Articles
Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity. Kim HK, Min S, Song M, Jung S, Choi JW, Kim Y, Lee S, Yoon S, Kim HH. Nat Biotechnol. 2018 Mar;36(3):239-241. doi: 10.1038/nbt.4061. Epub 2018 Jan 29. PubMed
SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with high generalization performance. Kim HK, Kim Y, Lee S, Min S, Bae JY, Choi JW, Park J, Jung D, Yoon S, Kim HH. Sci Adv. 2019 Nov 6;5(11):eaax9249. doi: 10.1126/sciadv.aax9249. eCollection 2019 Nov. PubMed
Generalizable sgRNA design for improved CRISPR/Cas9 editing efficiency. Hiranniramol K, Chen Y, Liu W, Wang X. Bioinformatics. 2020 May 1;36(9):2684-2689. doi: 10.1093/bioinformatics/btaa041. PubMed
Predicting the efficiency of prime editing guide RNAs in human cells. Kim HK, Yu G, Park J, Min S, Lee S, Yoon S, Kim HH. Nat Biotechnol. 2020 Sep 21. pii: 10.1038/s41587-020-0677-y. doi: 10.1038/s41587-020-0677-y. PubMed

Associated Plasmids
Recording of elapsed time and temporal information about biological events using Cas9. Park J, Lim JM, Jung I, Heo SJ, Park J, Chang Y, Kim HK, Jung D, Yu JH, Min S, Yoon S, Cho SR, Park T, Kim HH. Cell. 2021 Jan 28. pii: S0092-8674(21)00014-3. doi: 10.1016/j.cell.2021.01.014. PubMed

Associated Plasmids
Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens. Marquart KF, Allam A, Janjuha S, Sintsova A, Villiger L, Frey N, Krauthammer M, Schwank G. Nat Commun. 2021 Aug 25;12(1):5114. doi: 10.1038/s41467-021-25375-z. PubMed
Replacing the SpCas9 HNH domain by deaminases generates compact base editors with an alternative targeting scope. Villiger L, Schmidheini L, Mathis N, Rothgangl T, Marquart K, Schwank G. Mol Ther Nucleic Acids. 2021 Aug 26;26:502-510. doi: 10.1016/j.omtn.2021.08.025. eCollection 2021 Dec 3. PubMed

Associated Plasmids
High-throughput functional evaluation of human cancer-associated mutations using base editors. Kim Y, Lee S, Cho S, Park J, Chae D, Park T, Minna JD, Kim HH. Nat Biotechnol. 2022 Jun;40(6):874-884. doi: 10.1038/s41587-022-01276-4. Epub 2022 Apr 11. PubMed
Predicting prime editing efficiency and product purity by deep learning. Mathis N, Allam A, Kissling L, Marquart KF, Schmidheini L, Solari C, Balazs Z, Krauthammer M, Schwank G. Nat Biotechnol. 2023 Jan 16. doi: 10.1038/s41587-022-01613-7. PubMed

Associated Plasmids
Prediction of prime editing insertion efficiencies using sequence features and DNA repair determinants. Koeppel J, Weller J, Peets EM, Pallaseni A, Kuzmin I, Raudvere U, Peterson H, Liberante FG, Parts L. Nat Biotechnol. 2023 Feb 16. doi: 10.1038/s41587-023-01678-y. PubMed
Prediction of efficiencies for diverse prime editing systems in multiple cell types. Yu G, Kim HK, Park J, Kwak H, Cheong Y, Kim D, Kim J, Kim J, Kim HH. Cell. 2023 Apr 21:S0092-8674(23)00331-8. doi: 10.1016/j.cell.2023.03.034. PubMed

Associated Plasmids
Continuous directed evolution of a compact CjCas9 variant with broad PAM compatibility. Schmidheini L, Mathis N, Marquart KF, Rothgangl T, Kissling L, Bock D, Chanez C, Wang JP, Jinek M, Schwank G. Nat Chem Biol. 2023 Sep 21. doi: 10.1038/s41589-023-01427-x. PubMed

Associated Plasmids
Enhancing prime editor activity by directed protein evolution in yeast. Weber Y, Bock D, Ivascu A, Mathis N, Rothgangl T, Ioannidi EI, Blaudt AC, Tidecks L, Vadovics M, Muramatsu H, Reichmuth A, Marquart KF, Kissling L, Pardi N, Jinek M, Schwank G. Nat Commun. 2024 Mar 7;15(1):2092. doi: 10.1038/s41467-024-46107-z. PubMed

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