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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Designing of peptides with desired half-life in intestine-like environment
|
|---|---|
| Published in |
BMC Bioinformatics, August 2014
|
| DOI | 10.1186/1471-2105-15-282 |
| Pubmed ID | |
| Authors |
Arun Sharma, Deepak Singla, Mamoon Rashid, Gajendra Pal Singh Raghava |
| Abstract |
In past, a number of peptides have been reported to possess highly diverse properties ranging from cell penetrating, tumor homing, anticancer, anti-hypertensive, antiviral to antimicrobials. Owing to their excellent specificity, low-toxicity, rich chemical diversity and availability from natural sources, FDA has successfully approved a number of peptide-based drugs and several are in various stages of drug development. Though peptides are proven good drug candidates, their usage is still hindered mainly because of their high susceptibility towards proteases degradation. We have developed an in silico method to predict the half-life of peptides in intestine-like environment and to design better peptides having optimized physicochemical properties and half-life. |
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 % |
|---|---|---|
| India | 1 | 50% |
| Norway | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 2% |
| Germany | 1 | <1% |
| Unknown | 105 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 19% |
| Student > Master | 15 | 14% |
| Researcher | 13 | 12% |
| Student > Bachelor | 10 | 9% |
| Student > Doctoral Student | 7 | 6% |
| Other | 14 | 13% |
| Unknown | 28 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 30 | 28% |
| Biochemistry, Genetics and Molecular Biology | 22 | 20% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 6% |
| Chemistry | 6 | 6% |
| Immunology and Microbiology | 4 | 4% |
| Other | 11 | 10% |
| Unknown | 29 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 23 August 2023.
All research outputs
#6,739,488
of 24,483,002 outputs
Outputs from BMC Bioinformatics
#2,437
of 7,544 outputs
Outputs of similar age
#61,077
of 240,340 outputs
Outputs of similar age from BMC Bioinformatics
#48
of 119 outputs
Altmetric has tracked 24,483,002 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,544 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 67% 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 240,340 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 74% of its contemporaries.
We're also able to compare this research output to 119 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 59% of its contemporaries.