Visualizing mutations at the level of single cells
BioSpektrum, ISSN: 1868-6249, Vol: 26, Issue: 4, Page: 388-390
2020
- 1Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures1
- Readers1
Article Description
Bacterial mutations have been investigated since many years, but they remain difficult to observe directly in single cells, which limits the analysis of the underlying molecular mechanism. However, for the investigation of mutations at the level of single cells, precise analytical tools are currently developed. This article describes a workflow for visualizing mutations in single cells and lays the foundation for the quantification of bacterial mutation rates in the future.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85086859866&origin=inward; http://dx.doi.org/10.1007/s12268-020-1414-2; https://link.springer.com/10.1007/s12268-020-1414-2; https://link.springer.com/content/pdf/10.1007/s12268-020-1414-2.pdf; https://link.springer.com/article/10.1007/s12268-020-1414-2/fulltext.html; https://dx.doi.org/10.1007/s12268-020-1414-2; https://link.springer.com/article/10.1007/s12268-020-1414-2
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know