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Predicting AID off-targets: A step forward
In this issue of JEM, Álvarez-Prado et al. (https://doi.org/10.1084/jem.20171738) designed a DNA capture library allowing them to identify 275 genes targeted by AID in mouse germinal center B cells. Using the molecular features of these genes to feed a machine-learning algorithm, they determined tha...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Rockefeller University Press
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5839771/ https://www.ncbi.nlm.nih.gov/pubmed/29449308 http://dx.doi.org/10.1084/jem.20180231 |
| _version_ | 1783304458963255296 |
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| author | Reynaud, Claude-Agnès Weill, Jean-Claude |
| author_facet | Reynaud, Claude-Agnès Weill, Jean-Claude |
| author_sort | Reynaud, Claude-Agnès |
| collection | PubMed |
| description | In this issue of JEM, Álvarez-Prado et al. (https://doi.org/10.1084/jem.20171738) designed a DNA capture library allowing them to identify 275 genes targeted by AID in mouse germinal center B cells. Using the molecular features of these genes to feed a machine-learning algorithm, they determined that high-density RNA PolII and Spt5 binding—found in 2.3% of the genes—are the best predictors of AID specificity. |
| format | Online Article Text |
| id | pubmed-5839771 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2018 |
| publisher | Rockefeller University Press |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-58397712018-09-05 Predicting AID off-targets: A step forward Reynaud, Claude-Agnès Weill, Jean-Claude J Exp Med News In this issue of JEM, Álvarez-Prado et al. (https://doi.org/10.1084/jem.20171738) designed a DNA capture library allowing them to identify 275 genes targeted by AID in mouse germinal center B cells. Using the molecular features of these genes to feed a machine-learning algorithm, they determined that high-density RNA PolII and Spt5 binding—found in 2.3% of the genes—are the best predictors of AID specificity. Rockefeller University Press 2018-03-05 /pmc/articles/PMC5839771/ /pubmed/29449308 http://dx.doi.org/10.1084/jem.20180231 Text en © 2018 Reynaud and Weill http://www.rupress.org/terms/https://creativecommons.org/licenses/by-nc-sa/4.0/This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms/). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 4.0 International license, as described at https://creativecommons.org/licenses/by-nc-sa/4.0/). |
| spellingShingle | News Reynaud, Claude-Agnès Weill, Jean-Claude Predicting AID off-targets: A step forward |
| title | Predicting AID off-targets: A step forward |
| title_full | Predicting AID off-targets: A step forward |
| title_fullStr | Predicting AID off-targets: A step forward |
| title_full_unstemmed | Predicting AID off-targets: A step forward |
| title_short | Predicting AID off-targets: A step forward |
| title_sort | predicting aid off-targets: a step forward |
| topic | News |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5839771/ https://www.ncbi.nlm.nih.gov/pubmed/29449308 http://dx.doi.org/10.1084/jem.20180231 |
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