University of Heidelberg
Faculty of Medicine Mannheim
University Hospital Mannheim
CKM receives DFG funding for Project "Prdiktion von Therapieansprechen und Outcome beim lokal fortgeschrittenen Rektum-Karzinom mittels Radiomics und Deep Learning: eine beispielhafte Anwendung fr eine allgemein verwendbare, Deep Learning basierte Prozessierungs-Pipeline fr die Bild-Klassifikation" read more.
Alena-Kathrin Schnurr presented on our research on AI in medical imaging @ Research Plus forum
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Dr. Mathias Davids wins the I. I. Rabi Award of the International Society for Magnetic Resonance in Medicine (ISMRM),
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{C}alculating {R}esidue {F}lexibility {I}nformation from {S}tatistics and {E}nergy based {P}rediction

F. Zöllner, S. Neumann, K. Koch, F. Kummert and G. Sagerer

European Conference on Computational Biology 2002, Poster Abstracts,, pp.275-276

Fast Docking algorithms usually employ the rigid-body assumption \citeAck98,ewing2001. They score geometric complementarity as well as physico-chemical features. However, for unbound protein docking steric clashes might impose wrong penalization if side-chains change their conformation during the docking process. Using elasticity information obtained through energy calculations and statistics, we introduce a flexibility measure that combines the two. We reduce the influence of steric clash for side chains that are likely to change when scoring docking constellations.

Contact: Prof. Dr. Frank Zöllner last modified: 21.09.2020
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