What we do
We develop statistical and computational methods to answer biological questions from big data, from genomic sequence data to images. Our work is motivated by both the wealth of biological data currently being generated, as well as by the observation that dedicated models are often required to answer long-standing questions in biology.
We work closely with our collaborators from many areas of biology and interact equally closely with research groups in statistics and computer science to push our approaches beyond the state-of-the-art in the field. A particular focus of our work is on the analysis of low-depth sequencing data, including ancient DNA data, which we use to characterize human (pre-)history and to inform nature conservation.
Main publications 2019
- Wegmann D & Leuenberger C
Statistical Modeling and Inference in Genetics
Handbook of Statistical Genomics, doi: 10.1002/9781119487845.ch1 - Gros-Balthazard M et al.
Evolutionary transcriptomics reveals the origins of olives and the genomic changes associated with their domestication
The Plant Journal, doi: 10.1111/tpj.14435 - Bresadola L et al.
Admixture mapping in interspecific Populus hybrids identifies classes of genomic architectures for phytochemical, morphological and growth traits
New Phytologist, doi: 10.1111/nph.15930
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