Research

The lab's research is driven by a conviction that protein and DNA sequences encode a significant core of information about the ultimate structure and function of genetic material and its gene products. Research goals of the lab involve using protein and DNA sequences along with evolutionary information to predict a protein's: overall function, interaction partners, secondary structure, disordered regions, subcellular localization, membrane spanning protein structure, intra-chain residue contacts, cell cycle control, and domain boundaries. Another significant research focus is to improve the effectiveness and efficiency of structural genomics projects' ability to determine the structures of proteins on a large scale.

Summary

Our main goal is to predict important aspects of protein structure and function using sequence information, evolutionary information and results from other predictions. We apply whichever type of algorithm is needed to solve a problem from modern machine learning (neural networks, SVMs, tree-algorithms, Bayesian classifiers) to established statistical means.

Protein Prediction

The lab's research is driven by a conviction that protein and DNA sequences encode a significant core of information about the ultimate structure and function of genetic material and its gene products. Research goals of the lab involve using protein and DNA sequences along with evolutionary information to predict aspects of the proteins relevant to the advance of biomedical research. Examples are the prediction of coarse-grained aspects of protein function such as the type of enzymatic activity (ECGO), the prediction of interaction partners (Interaction Sites, DISIS, PiNAT), subcellular localization (LOCtree, LOCnet, PredictNLS), and of functional effects of point mutations/SNPs (SNAP), the prediction of disordered regions (NORSp, Ucon, IUcon), membrane spanning segments (PROF/PHDhtm), aspects of protein secondary structure (PROF/PHD, DSSPcont) and solvent accessibility (PROF/PHD), internal residue-residue contacts (PROFcon), the identification of domain-like functional and structural subunits (CHOP, CHOPnet), as well as the clustering of proteins into families (CHOP).