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GPU-based Cloud Computing for Comparing the Structure of Protein Binding Sites

Matthias Leinweber, Lars Baumgartner, Marco Mernberger, Thomas Fober, Eyke Hullermeier, Gerhard Klebe, Bernd Freisleben
Department of Mathematics & Computer Science and Center for Synthetic Microbiology, University of Marburg, Hans-Meerwein-Str. 3, D-35032 Marburg, Germany
IEEE Conference on Digital Ecosystem Technologies – Complex Environment Engineering, 2012

@article{leinweber2012gpu,

   title={GPU-based Cloud Computing for Comparing the Structure of Protein Binding Sites},

   author={Leinweber, M. and Baumg{"a}rtner, L. and Mernberger, M. and Fober, T. and H{"u}llermeier, E. and Klebe, G. and Freisleben, B.},

   year={2012}

}

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In this paper, we present a novel approach for using a GPU-based Cloud computing infrastructure to efficiently perform a structural comparison of protein binding sites. The original CPU-based Java version of a recent graph-based algorithm called SEGA has been rewritten in OpenCL to run on NVIDIA GPUs in parallel on a set of Amazon EC2 Cluster GPU Instances. This new implementation of SEGA has been tested on a subset of protein structure data contained in the CavBase, providing a structural comparison of protein binding sites on a much larger scale than in previous research efforts reported in the literature.
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