<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
doi: 10.1113/ep086864
pmid: 29603460
Genome editing enables precise changes to be made in the genome of living cells. The technique was originally developed in the 1980’s but largely limited to use in mice. The discovery that a targeted double stranded break (DSB) at a unique site in the genome, close to the site to be changed, could substantially increase the efficiency of editing raised the possibility of using the technique in a broader range of animal models and potentially human cells. But the challenge was to identify reagents that could create targeted breaks at a unique genomic location with minimal off-target effects. In 2005, the demonstration that programmable zinc finger nucleases (ZFNs) could perform this task, led to a number of proof-of-concept studies, but a limitation was the ease with which effective ZFNs could be produced. In 2009, the development of TAL-effector nucleases (TALENs) increased the specificity of gene editing and the ease of design and production. However, it wasn’t until 2013 and the development of the CRISPR Cas9/guideRNA that gene editing became a research tool that any lab could use.
Gene Editing, Science & Technology, Physiology, RNA, Guide, CRISPR-Cas Systems, Gene Expression Regulation, Mutation, Animals, Humans, Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR-Cas Systems, Life Sciences & Biomedicine
Gene Editing, Science & Technology, Physiology, RNA, Guide, CRISPR-Cas Systems, Gene Expression Regulation, Mutation, Animals, Humans, Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR-Cas Systems, Life Sciences & Biomedicine
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
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. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |