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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Enzyme Nicotinamide Cofactor Specificity Reversal Guided by Automated Structural Analysis and Library Design
|
|---|---|
| Chapter number | 2 |
| Book title |
Synthetic Metabolic Pathways
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7295-1_2 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7294-4, 978-1-4939-7295-1
|
| Authors |
Jackson K. B. Cahn, Sabine Brinkmann-Chen, Frances H. Arnold, Cahn, Jackson K. B., Brinkmann-Chen, Sabine, Arnold, Frances H. |
| Abstract |
The specificity of enzymes for nicotinamide adenine dinucleotide (NAD) or nicotinamide adenine dinucleotide phosphate (NADP) as redox carriers can pose a significant hurdle for metabolic engineering and synthetic biology applications, where switching the specificity might be beneficial. We have developed an easy-to-use computational tool (CSR-SALAD) for the design of mutant libraries to simplify the process of reversing the cofactor specificity of an enzyme. Here, we describe the optimal use of this tool and present methods for its application in a laboratory setting. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 21% |
| Researcher | 3 | 21% |
| Other | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Professor | 1 | 7% |
| Other | 3 | 21% |
| Unknown | 2 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 36% |
| Chemical Engineering | 2 | 14% |
| Chemistry | 2 | 14% |
| Agricultural and Biological Sciences | 1 | 7% |
| Social Sciences | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 2 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 05 July 2018.
All research outputs
#18,576,855
of 23,008,860 outputs
Outputs from Methods in molecular biology
#7,962
of 13,157 outputs
Outputs of similar age
#330,487
of 442,295 outputs
Outputs of similar age from Methods in molecular biology
#950
of 1,498 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,157 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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 442,295 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.