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| Title |
Effect of conformation sampling strategies in genetic algorithm for multiple protein docking
|
|---|---|
| Published in |
BMC Proceedings, November 2012
|
| DOI | 10.1186/1753-6561-6-s7-s4 |
| Pubmed ID | |
| Authors |
Juan Esquivel-Rodríguez, Daisuke Kihara |
| Abstract |
Macromolecular protein complexes play important roles in a cell and their tertiary structure can help understand key biological processes of their functions. Multiple protein docking is a valuable computational tool for providing structure information of multimeric protein complexes. In a previous study we developed and implemented an algorithm for this purpose, named Multi-LZerD. This method represents a conformation of a multimeric protein complex as a graph, where nodes denote subunits and each edge connecting nodes denotes a pairwise docking conformation of the two subunits. Multi-LZerD employs a genetic algorithm to sample different topologies of the graph and pairwise transformations between subunits, seeking for the conformation of the optimal (lowest) energy. In this study we explore different configurations of the genetic algorithm, namely, the population size, whether to include a crossover operation, as well as the threshold for structural clustering, to find the optimal experimental setup. |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 6% |
| Unknown | 15 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 44% |
| Researcher | 4 | 25% |
| Student > Doctoral Student | 1 | 6% |
| Professor | 1 | 6% |
| Student > Bachelor | 1 | 6% |
| Other | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 63% |
| Computer Science | 5 | 31% |
| Chemistry | 1 | 6% |
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 November 2012.
All research outputs
#15,692,595
of 23,318,744 outputs
Outputs from BMC Proceedings
#216
of 379 outputs
Outputs of similar age
#114,304
of 180,668 outputs
Outputs of similar age from BMC Proceedings
#4
of 7 outputs
Altmetric has tracked 23,318,744 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 379 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.