A few weeks ago, I gave the Pande Group meeting. The slides are on github, and you can view them here. The title of the talk is Protein Folding is Easy: Towards Markov State Models for Conformational Change, and mostly addresses my learning distance metrics for kinetic clustering of protein conformations from molecular dynamics simulations. The central challenge here is detecting structurally subtle but slow conformational changes in a dataset that might contain massive structural changes, like folding. Simply clustering at a tiny radius with a standard distance metric (RMSD) is fine in theory, but fails in practice to deal with the bias-variance tradeoff effectively.

The slides are written in pure markdown and rendered to HTML5 using an adapted version of the google-io-2012 HTML5 slide deck. The slide deck is now a little python package, hosted on github. After installing it (python setup.py install), just run slidedeck create to get started with a new template deck, and slidedeck render to make some HTML5.