MicroRNA circuits for transcriptional logic
Methods in Molecular Biology, ISSN: 1064-3745, Vol: 813, Page: 169-186
2012
- 9Citations
- 22Captures
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
- Citations9
- Citation Indexes9
- CrossRef8
- Captures22
- Readers22
- 22
Book Chapter Description
One of the longstanding challenges in synthetic biology is rational design of complex regulatory circuitry with multiple biological inputs, complex internal processing, and physiologically active outputs. We have previously proposed how to address this challenge in the case of transcription factor inputs. Here we describe the methods used to construct these synthetic circuits, capable of performing logic integration of transcription factor inputs using microRNA expression vectors and RNA interference (RNAi). The circuits operate in mammalian cells and they can serve as starting point for more complex synthetic information processing networks in these cells. © 2012 Springer Science+Business Media, LLC.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=82355171271&origin=inward; http://dx.doi.org/10.1007/978-1-61779-412-4_10; http://www.ncbi.nlm.nih.gov/pubmed/22083742; https://link.springer.com/10.1007/978-1-61779-412-4_10; https://doi.org/10.1007%2F978-1-61779-412-4_10; http://www.springerlink.com/index/10.1007/978-1-61779-412-4_10; http://www.springerlink.com/index/pdf/10.1007/978-1-61779-412-4_10; https://dx.doi.org/10.1007/978-1-61779-412-4_10; https://link.springer.com/protocol/10.1007/978-1-61779-412-4_10
Springer Science and Business Media LLC
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