| Title |
In silico regulatory analysis for exploring human disease progression
|
|---|---|
| Published in |
Biology Direct, June 2008
|
| DOI | 10.1186/1745-6150-3-24 |
| Pubmed ID | |
| Authors |
Dustin T Holloway, Mark Kon, Charles DeLisi |
| Abstract |
An important goal in bioinformatics is to unravel the network of transcription factors (TFs) and their targets. This is important in the human genome, where many TFs are involved in disease progression. Here, classification methods are applied to identify new targets for 152 transcriptional regulators using publicly-available targets as training examples. Three types of sequence information are used: composition, conservation, and overrepresentation. |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 15% |
| France | 1 | 4% |
| Unknown | 21 | 81% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 27% |
| Researcher | 6 | 23% |
| Other | 3 | 12% |
| Professor > Associate Professor | 2 | 8% |
| Student > Master | 2 | 8% |
| Other | 5 | 19% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 38% |
| Biochemistry, Genetics and Molecular Biology | 4 | 15% |
| Medicine and Dentistry | 3 | 12% |
| Unspecified | 1 | 4% |
| Nursing and Health Professions | 1 | 4% |
| Other | 6 | 23% |
| Unknown | 1 | 4% |