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Data-driven computational molecular biology


Our goals are the design and implementation of algorithms solving problems in computational molecular biology. Main topic is the development of tools for protein design. In many cases, we utilise knowledge-based potentials deduced from large data sets like multiple sequence alignments (MSAs). In addition, we are interested in analysing the content of microbial genomes and protein evolution.

We offer the following online tools:

Web Service

H2r (predicting evolutionary relevant residues from MSAs)

Additional Tools, developed in cooperation with other groups

SIGI-HMM (predicting genomic islands)

GCB-Scores (predicting highly expressed genes)

YACOP (gene prediction)

  1. Fakultät für Biologie und Vorklinische Medizin
  2. Faculty Research

Computational Protein Design and Evolution

Group of
adj. Prof. Dr. R. Merkl

 

 

Rm Animated

We are interested in understanding the function of proteins by utilizing in silico methods. Often, it is helpful to project additional data onto the 3D structure of a protein.