Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease

Research output: Contribution to journalJournal articleResearchpeer-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 languageEnglish
JournalP L o S One
Issue number1
Pages (from-to)e16542
Publication statusPublished - 1 Jan 2011

    Research areas

  • 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

ID: 33021306