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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Challenges to Ensure a Better Translation of Metabolic Engineering for Industrial Applications
|
|---|---|
| Chapter number | 1 |
| Book title |
Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology
|
| Published in |
Methods in molecular biology, January 2023
|
| DOI | 10.1007/978-1-0716-2617-7_1 |
| Pubmed ID | |
| Book ISBNs |
978-1-07-162616-0, 978-1-07-162617-7
|
| Authors |
Daboussi, Fayza, Lindley, Nic D. |
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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 33% |
| Researcher | 2 | 17% |
| Professor > Associate Professor | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 25% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Chemical Engineering | 1 | 8% |
| Agricultural and Biological Sciences | 1 | 8% |
| Engineering | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 5 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 13 October 2022.
All research outputs
#15,291,427
of 23,515,383 outputs
Outputs from Methods in molecular biology
#4,891
of 13,376 outputs
Outputs of similar age
#214,423
of 435,204 outputs
Outputs of similar age from Methods in molecular biology
#150
of 491 outputs
Altmetric has tracked 23,515,383 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,376 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 58% 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 435,204 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 491 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.