You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
| Title |
Defining structural and evolutionary modules in proteins: a community detection approach to explore sub-domain architecture
|
|---|---|
| Published in |
BMC Molecular and Cell Biology, October 2013
|
| DOI | 10.1186/1472-6807-13-20 |
| Pubmed ID | |
| Authors |
Jose Sergio Hleap, Edward Susko, Christian Blouin |
| Abstract |
Assessing protein modularity is important to understand protein evolution. Still the question of the existence of a sub-domain modular architecture remains. We propose a graph-theory approach with significance and power testing to identify modules in protein structures. In the first step, clusters are determined by optimizing the partition that maximizes the modularity score. Second, each cluster is tested for significance. Significant clusters are referred to as modules. Evolutionary modules are identified by analyzing homologous structures. Dynamic modules are inferred from sets of snapshots of molecular simulations. We present here a methodology to identify sub-domain architecture robustly, biologically meaningful, and statistically supported. |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 2% |
| India | 1 | 2% |
| Unknown | 60 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 26 | 42% |
| Student > Ph. D. Student | 11 | 18% |
| Researcher | 8 | 13% |
| Other | 4 | 6% |
| Professor | 3 | 5% |
| Other | 6 | 10% |
| Unknown | 4 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 31 | 50% |
| Agricultural and Biological Sciences | 13 | 21% |
| Biochemistry, Genetics and Molecular Biology | 7 | 11% |
| Psychology | 3 | 5% |
| Physics and Astronomy | 2 | 3% |
| Other | 2 | 3% |
| Unknown | 4 | 6% |