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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mixed-mode resins: taking shortcut in downstream processing of raw-starch digesting α-amylases
|
|---|---|
| Published in |
Scientific Reports, October 2015
|
| DOI | 10.1038/srep15772 |
| Pubmed ID | |
| Authors |
Nikola Lončar, Marinela Šokarda Slavić, Zoran Vujčić, Nataša Božić |
| Abstract |
Bacillus licheniformis 9945a α-amylase is known as a potent enzyme for raw starch hydrolysis. In this paper, a mixed mode Nuvia cPrime™ resin is examined with the aim to improve the downstream processing of raw starch digesting amylases and exploit the hydrophobic patches on their surface. This resin combines hydrophobic interactions with cation exchange groups and as such the presence of salt facilitates hydrophobic interactions while the ion-exchange groups enable proper selectivity. α-Amylase was produced using an optimized fed-batch approach in a defined media and significant overexpression of 1.2 g L(-1) was achieved. This single step procedure enables simultaneous concentration, pigment removal as well as purification of amylase with yields of 96% directly from the fermentation broth. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Serbia | 1 | 5% |
| Unknown | 19 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 20% |
| Other | 2 | 10% |
| Student > Doctoral Student | 2 | 10% |
| Student > Ph. D. Student | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Other | 2 | 10% |
| Unknown | 6 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 25% |
| Agricultural and Biological Sciences | 3 | 15% |
| Chemical Engineering | 2 | 10% |
| Computer Science | 1 | 5% |
| Chemistry | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 7 | 35% |
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 08 December 2015.
All research outputs
#18,432,465
of 22,835,198 outputs
Outputs from Scientific Reports
#93,280
of 123,302 outputs
Outputs of similar age
#204,175
of 283,603 outputs
Outputs of similar age from Scientific Reports
#2,016
of 2,662 outputs
Altmetric has tracked 22,835,198 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 123,302 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one is in the 14th percentile – i.e., 14% 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 283,603 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2,662 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.