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Mendeley readers
Attention Score in Context
| Title |
A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli
|
|---|---|
| Published in |
BMC Bioinformatics, May 2014
|
| DOI | 10.1186/1471-2105-15-134 |
| Pubmed ID | |
| Authors |
Narjeskhatoon Habibi, Siti Z Mohd Hashim, Alireza Norouzi, Mohammed Razip Samian |
| Abstract |
Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and economic volume. Although logical strategies of genetic engineering have been established, protein overexpression is still an art. In particular, heterologous expression is often hindered by low level of production and frequent fail due to opaque reasons. The problem is accentuated because there is no generic solution available to enhance heterologous overexpression. For a given protein, the extent of its solubility can indicate the quality of its function. Over 30% of synthesized proteins are not soluble. In certain experimental circumstances, including temperature, expression host, etc., protein solubility is a feature eventually defined by its sequence. Until now, numerous methods based on machine learning are proposed to predict the solubility of protein merely from its amino acid sequence. In spite of the 20 years of research on the matter, no comprehensive review is available on the published methods. |
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 % |
|---|---|---|
| Norway | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 152 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | <1% |
| Czechia | 1 | <1% |
| Switzerland | 1 | <1% |
| Unknown | 149 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 38 | 25% |
| Researcher | 30 | 20% |
| Student > Master | 11 | 7% |
| Student > Bachelor | 10 | 7% |
| Student > Doctoral Student | 7 | 5% |
| Other | 17 | 11% |
| Unknown | 39 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 37 | 24% |
| Biochemistry, Genetics and Molecular Biology | 34 | 22% |
| Computer Science | 10 | 7% |
| Chemistry | 8 | 5% |
| Chemical Engineering | 6 | 4% |
| Other | 16 | 11% |
| Unknown | 41 | 27% |
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 09 May 2014.
All research outputs
#18,371,959
of 22,755,127 outputs
Outputs from BMC Bioinformatics
#6,302
of 7,269 outputs
Outputs of similar age
#164,340
of 227,621 outputs
Outputs of similar age from BMC Bioinformatics
#110
of 145 outputs
Altmetric has tracked 22,755,127 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 7,269 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 227,621 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 145 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.