Project Team Leader: Ludwig Geistlinger, PhD
CCB’s Computational biology group aims at building sustainable tools and integrated data science products that empower experimental data-generating groups to explore, analyze, and interpret their data. We have broad expertise in computational biology and biostatistics, with applications in single-cell and bulk RNA-seq analysis, gene set and network enrichment analysis and copy number variation analysis to name a few. We aim to provide experimental groups with data analysis competence regarding computational, statistical, and bioinformatic aspects. This also includes to enable researchers to easily put their datasets in context of existing databases of high-throughput genomic datasets. We work primarily in R and Python and deliver accessible, transparent, and reproducible solutions for complex data analysis tasks. Learn about some of our ongoing and previous collaborations below!
For questions about CCB’s Computational biology work group or to ask how CCB can help with your project, please email CCB.