| Title |
Biological Networks for Predicting Chemical Hepatocarcinogenicity Using Gene Expression Data from Treated Mice and Relevance across Human and Rat Species
|
|---|---|
| Published in |
PLOS ONE, May 2013
|
| DOI | 10.1371/journal.pone.0063308 |
| Pubmed ID | |
| Authors |
Reuben Thomas, Russell S. Thomas, Scott S. Auerbach, Christopher J. Portier |
| Abstract |
Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
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 | 4 | 29% |
| Other | 2 | 14% |
| Student > Postgraduate | 2 | 14% |
| Student > Ph. D. Student | 1 | 7% |
| Student > Bachelor | 1 | 7% |
| Other | 2 | 14% |
| Unknown | 2 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 21% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 14% |
| Agricultural and Biological Sciences | 2 | 14% |
| Mathematics | 1 | 7% |
| Other | 2 | 14% |
| Unknown | 2 | 14% |