| Title |
Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis
|
|---|---|
| Published in |
PLoS Computational Biology, March 2008
|
| DOI | 10.1371/journal.pcbi.1000043 |
| Pubmed ID | |
| Authors |
Ugo Ala, Rosario Michael Piro, Elena Grassi, Christian Damasco, Lorenzo Silengo, Martin Oti, Paolo Provero, Ferdinando Di Cunto |
| Abstract |
Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. |
Mendeley readers
The data shown below were compiled from readership statistics for 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 3% |
| United States | 3 | 2% |
| Italy | 3 | 2% |
| Germany | 2 | 1% |
| Australia | 1 | <1% |
| Czechia | 1 | <1% |
| Tunisia | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Greece | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 138 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 39 | 25% |
| Researcher | 34 | 22% |
| Student > Master | 17 | 11% |
| Professor > Associate Professor | 13 | 8% |
| Student > Bachelor | 10 | 6% |
| Other | 27 | 17% |
| Unknown | 16 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 72 | 46% |
| Computer Science | 21 | 13% |
| Biochemistry, Genetics and Molecular Biology | 19 | 12% |
| Medicine and Dentistry | 10 | 6% |
| Engineering | 3 | 2% |
| Other | 14 | 9% |
| Unknown | 17 | 11% |