23 Jan 2012
The action of genes is regulated through interactions with other genes. Understanding gene regulatory networks is therefore crucial to gain insight into the molecular mechanisms that underlie health and disease. Building such networks that involve thousands of genes and millions of interactions requires large-scale experimental datasets that in practice are affected by all kinds of artifacts. In particular when studying rare diseases of which the underlying biology is still largely unknown, the limited number of available samples further complicates the issue.
In a recent paper in PLoS Computational Biology, Seyed Yahya Anvar (Leiden University Medical Centre) and colleagues hypothesize that biologically relevant relationships between genes are often conserved across species and that interspecies gene networks should be more meaningful from a biological perspective. Working from this hypothesis, they develop the Dandelion algorithm to construct and train intraspecies Bayesian networks. They demonstrate their approach on a dataset comprising both animal model and human data on OPMD, a rare muscular disorder.
Anvar SY, Tucker A, Vinciotti V, Venema A, van Ommen GJB, van der Maarel SM, Raz V, 't Hoen PAC
Interspecies translation of disease networks increases robustness and predictive accuracy
PLoS Comput Biol 7(11):e1002258