My main interests are developing new statistical models and efficient computational implementations of general applicability. I have worked a lot on methods for imputation and phasing of genotypes, especially in the face of uncertainty (e.g. contaminated samples, low-coverage sequencing, with ancient DNA as a new exciting application area). My original applications were in plant and animal breeding, where pedigrees are available, but we are moving beyond that.
In another exciting collaboration, I am studying computational techniques for a challenging new imaging modality, “flash X-ray imaging”, which allows the study of individual proteins and other small biological particles at high resolution through exposure to very brief X-ray pulses at special X-ray free electron lasers. One facility exists at Stanford in the U.S., another is being constructed in Hamburg. In this case, the possible resolution attainable is also a matter of how to best treat noise and uncertainty, while getting reasonable results in reasonable time.
As a bit of a computer nerd at heart, I also enjoy the fact that this application leads us to use heterogeneous computing, e.g. GPUs. Very soon, we will all need to use more radical high performance approaches in life science data processing to be able to cope with the speed at which data is collected.
Kristiina Ausmees, PhD student
(Alberto Pietrini, PhD student, in Molecular biophysics group at ICM, UU)
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