Affiliation: Danish Institute of Agricultural Sciences
- A Bayesian variable selection procedure to rank overlapping gene setsAxel Skarman
Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Tjele DK 8830, Denmark
BMC Bioinformatics 13:73. 2012..We applied Bayesian variable selection to differential expression to prioritize the molecular and genetic pathways involved in the responses to Escherichia coli infection in Danish Holstein cows...
- Gene prioritization for livestock diseases by data integrationLi Jiang
Dept of Molecular Biology and Genetics, Aarhus Univ, Blichers alle 20, PO Box 50, DK 8830 Tjele, Denmark
Physiol Genomics 44:305-17. 2012..To our knowledge this is the first time that gene expression, ortholog mapping, protein interactions, and biomedical text data have been integrated systematically for ranking candidate genes in any livestock species...
- A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed recordsLi Jiang
Department of Molecular Biology and Genetics, Aarhus University, DK 8830 Tjele, Denmark
BMC Bioinformatics 15:315. 2014..Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization...
- Analysis of the real EADGENE data set: multivariate approaches and post analysis (open access publication)Peter Sørensen
University of Aarhus, Faculty of Agricultural Sciences, Dept of Genetics and Biotechnology, PO Box 50 DK 8830 Tjele, Denmark
Genet Sel Evol 39:651-68. 2007..The main result from these analyses was that gene sets involved in immune defence responses were differentially expressed...
- Gene expression profiling of liver from dairy cows treated intra-mammary with lipopolysaccharideLi Jiang
Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, University of Aarhus, DK 8830 Tjele, Denmark
BMC Genomics 9:443. 2008..coli lipopolysaccharide (LPS) treatment...
- Gene set analysis methods applied to chicken microarray expression dataAxel Skarman
Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, Aarhus University, DK 8830 Tjele, Denmark
BMC Proc 3:S8. 2009..Methods for predicting the possible annotations for genes with unknown function from the expression data at hand could be useful, but our results indicate that careful validation of the predictions is needed...