- Info
Rätsch Lab: Machine Learning in Biology
We are interested in modern machine learning techniques suitable for
the analysis of problems arising in genome biology and medicine, in particular cancer. We develop new learning techniques that
- are capable of dealing with large amounts of genomic/medical data,
- allow for very accurate predictions on the phenomenon at
hand and
- are able to comprehensibly provide reasons for their prognoses, and
thereby assist in gaining new insights.
Currently we work on accurate methods for
- RNA-seq-based transcriptome transcriptome reconstruction and analysis,
- on reannotating of families of genomes of a species and
- mapping expression as well as splicing QTLs.
We are furthermore interested in clinical data analysis and their integration with deep sequencing data.
Projects are supported by the
European Union, the
German Research Foundation, the
Sloan-Kettering Institute and the
Max-Planck Society.
We have several open postdoctoral positions (Details).