Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each paper is the result of many months of research, so we make a special effort to make them clear, beautiful and inspirational, and publish them in leading journals.
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MSPALF Scientific ReportsBayesian analysis of medical data
Bayesian networks describe the evolution of orthodontic features on patients receiving treatment versus no treatment for malocclusion.
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AANP Journal of the Royal Society InterfaceQuantifying noise in mass spectrometry and yeast two-hybrid protein interaction detection experiments
Protein detection experiments seek to measure for each pair of protein species whether they interact in any complex.
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GCPAMSJMLF PLoS ONE Networks for medical data
Network analysis of diagnostic data identifies combinations of the key factors which cause Class III malocclusion and how they evolve over time.
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AA Interface FocusWhat you see is not what you get: how sampling affects macroscopic features of biological networks
It is vital that we understand in detail how the topological characteristics of a real network relate to those of a finite random network.