Probabilistic modelling of metabolic regulation in prokaryotes
Meeting Room 2, CMS
Suprisingly little is known about regulatory processes in prokaryotes outside a small group of model species such as Escherichia coli. Probabilistic models can help to combine the comparatively sparse direct experimental evidence for regulation in less well known organisms such as Mycobacterium tuberculosis with gene expression data and results from the application of bioinformatics and genomic tools. I will discuss the challenges of such a project and some of the statistical concepts that might be useful for tackling them.
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