Statistical Computing and Mathematical Modeling
Progress in biology is driven by technology. High throughput sequencing and microscopy require sophisticated statistical and computational operations in order to exploit their potential. To understand (and, eventually, manipulate) biological systems, all available data about them need to be integrated into computable maps and mathematical models. Ideas and techniques from physics, mathematics, statistics, computer science and engineering are the crucial drivers for our research.
Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Michael I. Love, Wolfgang Huber, and Simon Anders. Genome Biology, 15(12):550, 2014.
Orchestrating high-throughput genomic analysis with Bioconductor. Wolfgang Huber, et al. Nature Methods, 12:115-121, 2015.
Data-driven hypothesis weighting increases detection power in big data analytics. Nikolaos Ignatiadis, Bernd Klaus, Judith Zaugg, Wolfgang Huber. http://biorxiv.org/content/early/2015/12/13/034330