Multi-organ whole-genome measurements and reverse engineering to uncover gene networks underlying complex traits

Jesper Tegner, Josefin Skogsberg, Johan Björkegren*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Together with computational analysis and modeling, the development of whole-genome measurement technologies holds the potential to fundamentally change research on complex disorders such as coronary artery disease. With these tools, the stage has been set to reveal the full repertoire of biological components (genes, proteins, and metabolites) in complex diseases and their interplay in modules and networks. Here we review how network identification based on reverse engineering, as applied to whole-genome datasets from simpler organisms, is now being adapted to more complex settings such as datasets from human cell lines and organs in relation to physiological and pathological states. Our focus is on the use of a systems biological approach to identify gene networks in coronary atherosclerosis. We also address how gene networks will probably play a key role in the development of early diagnostics and treatments for complex disorders in the coming era of individualized medicine.

Original languageEnglish (US)
Pages (from-to)267-277
Number of pages11
JournalJournal of Lipid Research
Volume48
Issue number2
DOIs
StatePublished - Feb 1 2007

Keywords

  • Computational modeling
  • Coronary atherosclerosis
  • Global gene expression
  • Individualized medicine
  • Multicellular disease

ASJC Scopus subject areas

  • Biochemistry
  • Endocrinology
  • Cell Biology

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