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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Optimizing complex phenotypes through model-guided multiplex genome engineering
|
|---|---|
| Published in |
Genome Biology, May 2017
|
| DOI | 10.1186/s13059-017-1217-z |
| Pubmed ID | |
| Authors |
Gleb Kuznetsov, Daniel B. Goodman, Gabriel T. Filsinger, Matthieu Landon, Nadin Rohland, John Aach, Marc J. Lajoie, George M. Church |
| Abstract |
We present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.∆A. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies. |
X Demographics
The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 38% |
| United Kingdom | 2 | 13% |
| Unknown | 8 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 63% |
| Scientists | 4 | 25% |
| Science communicators (journalists, bloggers, editors) | 2 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Unknown | 108 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 36 | 33% |
| Researcher | 21 | 19% |
| Student > Bachelor | 12 | 11% |
| Student > Master | 11 | 10% |
| Other | 7 | 6% |
| Other | 12 | 11% |
| Unknown | 10 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 41 | 38% |
| Agricultural and Biological Sciences | 28 | 26% |
| Chemical Engineering | 5 | 5% |
| Engineering | 4 | 4% |
| Medicine and Dentistry | 3 | 3% |
| Other | 13 | 12% |
| Unknown | 15 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 November 2020.
All research outputs
#2,379,155
of 25,394,764 outputs
Outputs from Genome Biology
#1,938
of 4,470 outputs
Outputs of similar age
#43,262
of 327,165 outputs
Outputs of similar age from Genome Biology
#44
of 67 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,165 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.