Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease
Research output: Contribution to journal › Journal article › Research › peer-review
Candidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.
| Original language | English |
|---|---|
| Journal | P L o S One |
| Volume | 6 |
| Issue number | 1 |
| Pages (from-to) | e16542 |
| ISSN | 1932-6203 |
| DOIs | |
| Publication status | Published - 1 Jan 2011 |
- Case-Control Studies, Computational Biology, Data Mining, Denmark, Diabetes Mellitus, Type 2, Fatty Liver, Humans, Metabolic Syndrome X, Middle Aged, Obesity, Phenotype, Polymorphism, Single Nucleotide, Protein Binding, Quantitative Trait Loci
Research areas
ID: 33021306