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X Demographics
Mendeley readers
| Title |
Using mathematical models to understand metabolism, genes, and disease
|
|---|---|
| Published in |
BMC Biology, September 2015
|
| DOI | 10.1186/s12915-015-0189-2 |
| Pubmed ID | |
| Authors |
H. Frederik Nijhout, Janet A. Best, Michael C. Reed |
| Abstract |
Mathematical models are a useful tool for investigating a large number of questions in metabolism, genetics, and gene-environment interactions. A model based on the underlying biology and biochemistry is a platform for in silico biological experimentation that can reveal the causal chain of events that connect variation in one quantity to variation in another. We discuss how we construct such models, how we have used them to investigate homeostatic mechanisms, gene-environment interactions, and genotype-phenotype mapping, and how they can be used in precision and personalized medicine. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Saudi Arabia | 1 | 17% |
| United Kingdom | 1 | 17% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 1 | 17% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| Brazil | 2 | 2% |
| Singapore | 1 | <1% |
| Unknown | 106 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 23% |
| Researcher | 23 | 21% |
| Student > Master | 10 | 9% |
| Professor > Associate Professor | 9 | 8% |
| Student > Bachelor | 8 | 7% |
| Other | 19 | 17% |
| Unknown | 17 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 18% |
| Biochemistry, Genetics and Molecular Biology | 17 | 15% |
| Medicine and Dentistry | 11 | 10% |
| Engineering | 8 | 7% |
| Mathematics | 8 | 7% |
| Other | 25 | 23% |
| Unknown | 22 | 20% |