Our goal is the design and implementation of algorithms solving problems in computational biology. Main topics are related to protein evolution and the development of tools for protein design. In many cases, we utilise knowledge-based potentials deduced from large data sets. We offer the following methods and datasets.

H2r (predicting residues important for protein function based on correlated mutations)
CLIPS-1D (predicting functionally and structurally important residue-positions based on 1D data)
CLIPS-4D (predicting functionally and structurally important residue-positions based on 1D and 3D data)
PresCont (predicting protein-protein interfaces)
GCB-Scores (predicting translational efficiency of genes)
for a whole genome(GCB4Genome) or individual genes (GCB4gene)

Key2Ann (Replacing database keys with a meaningful annotation)
GO4genome (whole genome phylogeny, source code and Y. pestis dataset)
PresCont (3D structures and MSAs for protein-protein complexes)
ENZ_LUCA (a dataset of MSAs and phylogenetic trees to study mutation-fixation)

SIGI-HMM (Predicting genomic islands, download)
YACOP (Enhanced gene prediction obtained by a combination of existing methods, download)