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.
Bayesian networks describe the evolution of orthodontic features on patients receiving treatment versus no treatment for malocclusion.
Quantifying 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.
Network analysis of diagnostic data identifies combinations of the key factors which cause Class III malocclusion and how they evolve over time.
It is vital that we understand in detail how the topological characteristics of a real network relate to those of a finite random network.