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Mendeley readers
| Title |
Pinpointing disease genes through phenomic and genomic data fusion
|
|---|---|
| Published in |
BMC Genomics, January 2015
|
| DOI | 10.1186/1471-2164-16-s2-s3 |
| Pubmed ID | |
| Authors |
Rui Jiang, Mengmeng Wu, Lianshuo Li |
| Abstract |
Pinpointing genes involved in inherited human diseases remains a great challenge in the post-genomics era. Although approaches have been proposed either based on the guilt-by-association principle or making use of disease phenotype similarities, the low coverage of both diseases and genes in existing methods has been preventing the scan of causative genes for a significant proportion of diseases at the whole-genome level. |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Unknown | 31 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 22% |
| Researcher | 7 | 22% |
| Other | 3 | 9% |
| Student > Bachelor | 2 | 6% |
| Student > Master | 2 | 6% |
| Other | 5 | 16% |
| Unknown | 6 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 16% |
| Agricultural and Biological Sciences | 5 | 16% |
| Computer Science | 5 | 16% |
| Engineering | 3 | 9% |
| Medicine and Dentistry | 3 | 9% |
| Other | 3 | 9% |
| Unknown | 8 | 25% |