Gidskehaug, Lars

Postdoc

E-mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Phone: +47-6496-5174

Present position: Postdoc at CIGENE/IHA, UMB

Degrees: PhD in bioinformatics/chemometrics at the Norwegian University of Science and Technology (NTNU), 2007. MSc in physical chemistry at NTNU, 2002.

Professional background: Postdoc CIGENE/IHA, UMB (2007-), PhD NTNU (2003-2007)

Research experience: Method development, specifically for variable (gene) selection based on microarray data. Validation of selection procedures.

Current research activity: Analysis of salmon SNP-data, with the aim of constructing a dense linkage map of the salmon genome, and mapping QTL of importance for the aquaculture industry. The work involves normalization and pre-processing, followed by clustering of SNP-data and calling of genotypes. Recent focus has been on resolving difficulties relating to the partly duplicated genome of salmonid fishes. Other projects include validation of a mathematical model describing the pigment uptake in salmon, analysis of pooled DNA-data, and investigation of salmon heart-shapes.

Selected publications:

  • Gidskehaug, L., et al., A framework for significance analysis of gene expression data using dimension reduction methods. BMC Bioinformatics, 2007. 8: p. 346.
  • Færgestad, E.M., et al., Pixel-based analysis of multiple images for the identification of changes: A novel approach applied to unravel proteome patterns of 2-D electrophoresis gel images. Proteomics, 2007. 7: p. 3450-3461.
  • Gidskehaug, L., Development of chemometric methods for variable selection on microarray data. 2007, Norwegian University of Science and Technology: Trondheim.
  • Gidskehaug, L., E. Anderssen, and B.K. Alsberg, Cross model validated feature selection based on gene clusters. Chemometr. Intell. Lab., 2006. 84: p. 172-176.
  • Martens, H., et al., Regression of a data matrix on descriptors of both its rows and of its columns via latent variables: L-PLSR. Comput. Stat. Data An., 2005. 48: p. 103-123.
  • Gidskehaug, L., et al., Bridge-PLS regression: two-block bilinear regression without deflation. J. Chemometr., 2004. 18: p. 208-215.
  • O'Sullivan, M.G., et al., Evaluation of pork colour: prediction of visual sensory quality of meat from instrumental and computer vision methods of colour analysis. Meat Sci., 2003. 65: p. 909-918.