| Title |
Pixels as ROIs (PAR): A Less-Biased and Statistically Powerful Approach for Gleaning Functional Information from Image Stacks
|
|---|---|
| Published in |
PLOS ONE, July 2013
|
| DOI | 10.1371/journal.pone.0069047 |
| Pubmed ID | |
| Authors |
Jacob Pearson Keller, Kazuaki Homma, Peter Dallos |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 7% |
| Unknown | 13 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 36% |
| Student > Ph. D. Student | 3 | 21% |
| Other | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Professor | 1 | 7% |
| Other | 2 | 14% |
| Unknown | 1 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 21% |
| Agricultural and Biological Sciences | 2 | 14% |
| Neuroscience | 2 | 14% |
| Psychology | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Other | 3 | 21% |
| Unknown | 2 | 14% |