| Title |
Learning “graph-mer” Motifs that Predict Gene Expression Trajectories in Development
|
|---|---|
| Published in |
PLoS Computational Biology, April 2010
|
| DOI | 10.1371/journal.pcbi.1000761 |
| Pubmed ID | |
| Authors |
Xuejing Li, Casandra Panea, Chris H. Wiggins, Valerie Reinke, Christina Leslie |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 7% |
| Germany | 1 | 2% |
| Brazil | 1 | 2% |
| France | 1 | 2% |
| Canada | 1 | 2% |
| India | 1 | 2% |
| Unknown | 49 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 34% |
| Student > Ph. D. Student | 17 | 29% |
| Professor > Associate Professor | 6 | 10% |
| Student > Master | 3 | 5% |
| Professor | 2 | 3% |
| Other | 5 | 9% |
| Unknown | 5 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 30 | 52% |
| Computer Science | 6 | 10% |
| Biochemistry, Genetics and Molecular Biology | 5 | 9% |
| Engineering | 4 | 7% |
| Mathematics | 3 | 5% |
| Other | 4 | 7% |
| Unknown | 6 | 10% |