| Title |
Unearthing the Root of Amino Acid Similarity
|
|---|---|
| Published in |
Journal of Molecular Evolution, June 2013
|
| DOI | 10.1007/s00239-013-9565-0 |
| Pubmed ID | |
| Authors |
James D. Stephenson, Stephen J. Freeland |
| Abstract |
Similarities and differences between amino acids define the rates at which they substitute for one another within protein sequences and the patterns by which these sequences form protein structures. However, there exist many ways to measure similarity, whether one considers the molecular attributes of individual amino acids, the roles that they play within proteins, or some nuanced contribution of each. One popular approach to representing these relationships is to divide the 20 amino acids of the standard genetic code into groups, thereby forming a simplified amino acid alphabet. Here, we develop a method to compare or combine different simplified alphabets, and apply it to 34 simplified alphabets from the scientific literature. We use this method to show that while different suggestions vary and agree in non-intuitive ways, they combine to reveal a consensus view of amino acid similarity that is clearly rooted in physico-chemistry. |
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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Israel | 1 | 2% |
| Australia | 1 | 2% |
| Unknown | 49 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 21% |
| Student > Master | 10 | 19% |
| Researcher | 10 | 19% |
| Student > Bachelor | 4 | 8% |
| Other | 4 | 8% |
| Other | 9 | 17% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 46% |
| Biochemistry, Genetics and Molecular Biology | 10 | 19% |
| Chemistry | 5 | 10% |
| Engineering | 3 | 6% |
| Physics and Astronomy | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 5 | 10% |
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 04 November 2013.
All research outputs
#17,285,668
of 25,374,647 outputs
Outputs from Journal of Molecular Evolution
#1,190
of 1,477 outputs
Outputs of similar age
#132,940
of 209,840 outputs
Outputs of similar age from Journal of Molecular Evolution
#4
of 5 outputs
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