Breakfast meeting on Computational Biology at AlbaNova
Monday 28 May 2012
to 09:00 at
Martin Lindén (Dept. of Biochemistry and Biophysics, Stockholm University)
Single molecule experiments have opened new windows to molecular biology by allowing us to follow individual proteins at work both in vitro and in vivo.
However, instrumental noise, cross-sample variations, and the inherent randomness of Brownian motion and low copy number chemistry often makes for noisy data that can be challenging to interpret. A very common problem is to analyze noisy time series with abrupt changes, reflecting for example binding events, or conformational changes in a protein complex.
In this talk, I will describe my ongoing attempts to tackle such problems with a combination of physical modeling and a machine learning technique known as ensemble learning or variational Bayes. In particular, I will discuss an application to in vitro DNA looping by the Lac repressor protein.