GSoC Projects26 Apr 2016
Fiona Naughton: Umbrella simulations with MDAnalysis
Umbrella Sampling is an MD technique which involves performing a series of simulations in which a reaction coordinate , such as the distance between two molecules, is restrained to different values. A method to analyse the combination of the simulations is weighted histogram analysis method (WHAM). Fiona will work on adding WHAM to the analysis module to calculate different observables.
Fiona Naughton is doing a PhD in Biochemistry at the University of Oxford with the Structural Bioinformatics and Computational Biochemistry Unit, studying protein/membrane interactions through molecular dynamics simulations. She has started her own blog and can be found on github under @fiona-naughton. She plans to continue to a career in the same field and outside academia enjoys reading, baking and handicraft.
John Detlefs: Dimensionality Reduction
MD-simulations produce data with several thousand dimensions, from which we want to learn something new about how proteins work and how they interact with each other. Fortunaly for us in a lot of cases one or two dimensions are enough to describe a specific function of a protein. Dimensionionality reduction algorithms help us to find projections into low dimensional subspaces that capture the relevant motions. John has chosen to implement principal component analysis and diffusion maps.
John Detlefs is a Mathematics and Chemistry double major at California Polytechnic State University, San Luis Obispo. His blog can be found on his website and on github he is @jdetle. When not contributing to MDAnalysis, John can be found reading a good book or enjoying one of the many outdoor activities California has to offer. After graduating in June 2016, John plans on pursuing a career in scientific computing.
In the next weeks they will both further refine their projects and setup personal blogs to update anyone interested about their progress during the summer. We plan to have all discussions public on the devel mailinglist.