Bioinformatics (Prof. Lenhof)March 9, 2023 2023-04-14 7:12
Bioinformatics (Prof. Lenhof)
The Lenhof group develops novel bioinformatics methods for topics and problems from biomedicine and pharmacy. We are designing algorithms and software for studying the molecular basis of diseases and for target identification. Moreover, we are working on novel approaches for biomarker detection and cancer diagnosis based on antibody and miRNA profiles. Another focal point is the study of molecular interactions, especially interactions between proteins and the development of innovative methods for protein docking. In order to accelerate the implementation of new approaches, we are developing BALL (Biochemical ALgorithms Library), a framework for rapid software prototyping in the area of Molecular Modeling and Bioinformatics.
Head of the Group
Prof. Dr. Hans-Peter Lenhof
Hans-Peter Lenhof studied mathematics and chemistry at Saarland University (Diploma in Mathematics 1989). He obtained a PhD in Computer Science from Saarland University in 1993. He worked as a PostDoc at the Max Planck Institute for Informatics in Saarbrücken from 1993 to 1999. In 1999, he obtained the ‘venia legendi’ (Habilitation) for Computer Science from Saarland University and became the head of a research group (C3) at the MPI for Informatics. In 2000, he became professor for bioinformatics at Saarland University.
“The focus of our research is on the development of novel bioinformatics approaches for elucidating and studying the mechanisms of tumor initiation and progression with the goal to improve the diagnosis, prognosis, and therapy of cancer.”
In collaboration with the group of Eckart Meese (Human Genetics, Saarland University), we are studying novel diagnostic approaches that are based on extensive autoantibody or miRNA signatures. In proof-of-principle studies, autoantibody or miRNA profiles of blood sera have been collected from a large number of diseased and unaffected persons. Classifiers that have been trained and evaluated on the resulting profiles obtained a high sensitivity and specificity for a large number of diseases among them meningioma, glioma, lung tumors, melanomas, and multiple sclerosis (MS). Our results provide clear evidence that comprehensive antibody and miRNA profiles have high diagnostic potential.
Analysis and Visualization of Biological Networks
Complex biological processes can be described as chains or networks of single reactions and can, hence, be modeled as graphs whose nodes and edges represent the involved biomolecules and their reactions and interactions. We are developing novel approaches for the analysis and visualization of biological processes based on network models. Here, we are especially interested in novel methods for the detection and analysis of deregulated signaling cascades associated with or caused by pathogenic processes.