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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Prediction of designer-recombinases for DNA editing with generative deep learning

Authors: Schmitt, Lukas Theo; Paszkowski-Rogacz, Maciej; Jug, Florian; Buchholz, Frank;

Prediction of designer-recombinases for DNA editing with generative deep learning

Abstract

Sequence data from "Prediction of designer-recombinases for DNA editing with generative deep learning" publication. Tyrosine site-specific recombinase gene sequences with the corresponding target sequences from already published projects. Recombinases were produced with directed evolution and sequenced with PacBio HiFi. The evolution of the recombinases sequences in this dataset were published in the following publications: https://doi.org/10.1126/science.1141453 https://doi.org/10.1038/nbt.3467 https://doi.org/10.1093/nar/gkz1078 https://doi.org/10.1038/s41467-022-28080-7

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Keywords

PacBio, Generative deep learning, Tyrosine site-specific recombinases, Sequencing, Protein sequence generation

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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