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.
The principal eigenvalue of small neutral networks determines their robustness, and is bounded by the logarithm of the number of vertices.
Properties of protein interaction networks test the reliability of data and hint at the underlying mechanism with which proteins recruit each other.
The immune system must simultaneously recall multiple defense strategies because many antigens can attack the host at the same time.
Associative networks with different loads model the ability of the immune system to respond simultaneously to multiple distinct antigen invasions.
Network analysis of diagnostic data identifies combinations of the key factors which cause Class III malocclusion and how they evolve over time.
Spectral analysis shows that disassortative networks exhibit a higher epidemiological threshold and are therefore easier to immunize.
Methods from tailored random graph theory reveal the relation between true biological networks and the often-biased samples taken from them.