Time-scale separation is one of the few systematic methods for eliminating internal complexity in biological systems, as originally introduced in enzyme kinetics by Michaelis and Menten. We will show how this basic idea can be formalised in a simple framework that can be applied to many biological contexts, including post-translational modification and gene regulation where combinatorial complexity has often impeded analysis. Surprisingly, the framework is entirely linear, despite being applied to highly nonlinear biochemical mechanisms.

New-generation sequencing data has transformed the biological sciences, allowing us to address research questions that previously were considered intractable.    In this talk I will discuss computational methods for analyzing such data, and discuss some applications to population genetic data. In one project we sequenced the exomes of representative Han Chinese and Tibetan humans to elucidate the genetic causes of altitude adaptation in Tibetans.  We show that selection on the EPAS1 gene can explain previously described physiological differences between Han Chinese individuals and Tibetans.  I will also discuss applications in other systems including other humans, such as the sequencing of the first Aboriginal Australian genome, and ancient DNA including Neanderthal DNA.

Abstract will be posted soon.

Epigenetics is the study of nonsequence-based changes, such as DNA
methylation, heritable during cell division. In this talk I will show
results relating DNA methylation to development and cancer, discovered
via examination of whole-genome measurements. The focus of the talk
will be on the statistical methods that permitted these discoveries:
both for microarrays and second generation sequencing data.