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dc.contributor.authorShah, Abhik
dc.contributor.authorTenzen, Toyoaki
dc.contributor.authorMcMahon, Andrew P.
dc.contributor.authorWoolf, Peter J
dc.date.accessioned2012-04-11T13:46:48Z
dc.date.issued2009
dc.identifier.citationShah, Abhik, Toyoaki Tenzen, Andrew P McMahon, and Peter J Woolf. 2009. Using mechanistic Bayesian networks to identify downstream targets of the Sonic Hedgehog pathway. BMC Bioinformatics 10: 433.en_US
dc.identifier.issn1471-2105en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:8531457
dc.description.abstractBackground: The topology of a biological pathway provides clues as to how a pathway operates, but rationally using this topology information with observed gene expression data remains a challenge. Results: We introduce a new general-purpose analytic method called Mechanistic Bayesian Networks (MBNs) that allows for the integration of gene expression data and known constraints within a signal or regulatory pathway to predict new downstream pathway targets. The MBN framework is implemented in an open-source Bayesian network learning package, the Python Environment for Bayesian Learning (PEBL). We demonstrate how MBNs can be used by modeling the early steps of the sonic hedgehog pathway using gene expression data from different developmental stages and genetic backgrounds in mouse. Using the MBN approach we are able to automatically identify many of the known downstream targets of the hedgehog pathway such as Gas1 and Gli1, along with a short list of likely targets such as Mig12. Conclusions: The MBN approach shown here can easily be extended to other pathways and data types to yield a more mechanistic framework for learning genetic regulatory models.en_US
dc.description.sponsorshipMolecular and Cellular Biologyen_US
dc.description.sponsorshipStem Cell and Regenerative Biologyen_US
dc.language.isoen_USen_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofdoi://10.1186/1471-2105-10-433en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3087349/pdf/en_US
dash.licenseLAA
dc.titleUsing Mechanistic Bayesian Networks to Identify Downstream Targets of the Sonic Hedgehog Pathwayen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalBMC Bioinformaticsen_US
dash.depositing.authorMcMahon, Andrew P.
dc.date.available2012-04-11T13:46:48Z
dc.identifier.doi10.1186/1471-2105-10-433*
dash.contributor.affiliatedMcMahon, Andrew P.


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