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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genetic algorithm with a crossover elitist preservation mechanism for protein–ligand docking
|
|---|---|
| Published in |
AMB Express, September 2017
|
| DOI | 10.1186/s13568-017-0476-0 |
| Pubmed ID | |
| Authors |
Boxin Guan, Changsheng Zhang, Jiaxu Ning |
| Abstract |
Protein-ligand docking plays an important role in computer-aided pharmaceutical development. Protein-ligand docking can be defined as a search algorithm with a scoring function, whose aim is to determine the conformation of the ligand and the receptor with the lowest energy. Hence, to improve an efficient algorithm has become a very significant challenge. In this paper, a novel search algorithm based on crossover elitist preservation mechanism (CEP) for solving protein-ligand docking problems is proposed. The proposed algorithm, namely genetic algorithm with crossover elitist preservation (CEPGA), employ the CEP to keep the elite individuals of the last generation and make the crossover more efficient and robust. The performance of CEPGA is tested on sixteen molecular docking complexes from RCSB protein data bank. In comparison with GA, LGA and SODOCK in the aspects of lowest energy and highest accuracy, the results of which indicate that the CEPGA is a reliable and successful method for protein-ligand docking problems. |
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 % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 15% |
| Student > Doctoral Student | 2 | 10% |
| Student > Ph. D. Student | 2 | 10% |
| Other | 1 | 5% |
| Unspecified | 1 | 5% |
| Other | 3 | 15% |
| Unknown | 8 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 15% |
| Computer Science | 2 | 10% |
| Chemistry | 2 | 10% |
| Agricultural and Biological Sciences | 1 | 5% |
| Unspecified | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 9 | 45% |
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 14 September 2017.
All research outputs
#15,479,632
of 23,002,898 outputs
Outputs from AMB Express
#446
of 1,240 outputs
Outputs of similar age
#198,576
of 316,290 outputs
Outputs of similar age from AMB Express
#13
of 33 outputs
Altmetric has tracked 23,002,898 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,240 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.