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Timeline
X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Machine Learning and Hybrid Methods for Metabolic Pathway Modeling
|
---|---|
Chapter number | 18 |
Book title |
Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology
|
Published in |
Methods in molecular biology, October 2022
|
DOI | 10.1007/978-1-0716-2617-7_18 |
Pubmed ID | |
Book ISBNs |
978-1-07-162616-0, 978-1-07-162617-7
|
Authors |
Miroslava Cuperlovic-Culf, Thao Nguyen-Tran, Steffany A. L. Bennett, Cuperlovic-Culf, Miroslava, Nguyen-Tran, Thao, Bennett, Steffany A. L. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 2 | 33% |
United States | 2 | 33% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 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 % |
---|---|---|
Researcher | 2 | 14% |
Student > Master | 2 | 14% |
Professor > Associate Professor | 1 | 7% |
Other | 1 | 7% |
Unspecified | 1 | 7% |
Other | 0 | 0% |
Unknown | 7 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 2 | 14% |
Biochemistry, Genetics and Molecular Biology | 2 | 14% |
Arts and Humanities | 1 | 7% |
Unspecified | 1 | 7% |
Unknown | 8 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 October 2022.
All research outputs
#13,329,938
of 23,885,338 outputs
Outputs from Methods in molecular biology
#3,316
of 13,512 outputs
Outputs of similar age
#156,728
of 427,331 outputs
Outputs of similar age from Methods in molecular biology
#48
of 214 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,512 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 75% 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 427,331 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 214 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.