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Nicolas Mathis

Showing results (11-20 of 20) with videos related to

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Nature Biotechnology|August 12, 2024
Publisher Correction: Machine learning prediction of prime editing efficiency across diverse chromatin contextsNicolas Mathis, Ahmed Allam, András Tálas, et al.
Nature Biotechnology|June 21, 2024
Machine learning prediction of prime editing efficiency across diverse chromatin contextsNicolas Mathis, Ahmed Allam, András Tálas, et al.
Nature Communications|March 7, 2024
Enhancing prime editor activity by directed protein evolution in yeastYanik Weber, Desirée Böck, Anastasia Ivașcu, et al.
Nature Methods|September 23, 2024
Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAsKim Fabiano Marquart, Nicolas Mathis, Amina Mollaysa, et al.
Biorxiv : the Preprint Server for Biology|December 31, 2025
LDLR variant classification through activity-normalized prime editing screeningPhillip J Zhou, Minja Velimirovic, Tian Yu, et al.
Molecular Cell|September 24, 2022
Stress-triggered hematopoietic stem cell proliferation relies on PrimPol-mediated reprimingKurt Jacobs, Cyril Doerdelmann, Jana Krietsch, et al.
Nature Biomedical Engineering|September 19, 2025
Spatial profiling of gene editing by in situ sequencing in mice and macaquesSharan Janjuha, Tatjana Haenggi, Thomas C Chamberlain, et al.
Genome Biology|May 9, 2025
Predicting adenine base editing efficiencies in different cellular contexts by deep learningLucas Kissling, Amina Mollaysa, Sharan Janjuha, et al.
Science (New York, N.Y.)|February 5, 2026
Programmable genome editing in human cells using RNA-guided bridge recombinasesOana Pelea, András Tálas, Javier Fernández Carrera, et al.
Blood|July 10, 2025
Boosting CAR T-Cell Efficacy by Blocking Proteasomal Degradation of Membrane AntigensLeonie Rieger, Kilian Irlinger, Franziska Füchsl, et al.
Pageof 2

Showing results (11-20 of 20) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 20 results.
Nature Biotechnology|August 12, 2024
Publisher Correction: Machine learning prediction of prime editing efficiency across diverse chromatin contextsNicolas Mathis, Ahmed Allam, András Tálas, et al.
Nature Biotechnology|June 21, 2024
Machine learning prediction of prime editing efficiency across diverse chromatin contextsNicolas Mathis, Ahmed Allam, András Tálas, et al.
Nature Communications|March 7, 2024
Enhancing prime editor activity by directed protein evolution in yeastYanik Weber, Desirée Böck, Anastasia Ivașcu, et al.
Nature Methods|September 23, 2024
Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAsKim Fabiano Marquart, Nicolas Mathis, Amina Mollaysa, et al.
Biorxiv : the Preprint Server for Biology|December 31, 2025
LDLR variant classification through activity-normalized prime editing screeningPhillip J Zhou, Minja Velimirovic, Tian Yu, et al.
Molecular Cell|September 24, 2022
Stress-triggered hematopoietic stem cell proliferation relies on PrimPol-mediated reprimingKurt Jacobs, Cyril Doerdelmann, Jana Krietsch, et al.
Nature Biomedical Engineering|September 19, 2025
Spatial profiling of gene editing by in situ sequencing in mice and macaquesSharan Janjuha, Tatjana Haenggi, Thomas C Chamberlain, et al.
Genome Biology|May 9, 2025
Predicting adenine base editing efficiencies in different cellular contexts by deep learningLucas Kissling, Amina Mollaysa, Sharan Janjuha, et al.
Science (New York, N.Y.)|February 5, 2026
Programmable genome editing in human cells using RNA-guided bridge recombinasesOana Pelea, András Tálas, Javier Fernández Carrera, et al.
Blood|July 10, 2025
Boosting CAR T-Cell Efficacy by Blocking Proteasomal Degradation of Membrane AntigensLeonie Rieger, Kilian Irlinger, Franziska Füchsl, et al.
Pageof 2