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Thursday, March 6 • 4:30pm - 6:30pm
Poster: Deformable Complex Network for Refining Low Resolution Structures, Chong Zhang, Rice University

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In macromolecular X-ray crystallography, it is often desirable to build more accurate atomic models based on lower resolution experimental diffraction data. In this study, we report a refinement algorithm called the deformable complex network (DCN), which is developed by including a novel angular-network-based restraint in target function in addition to what used in deformable elastic network (DEN) model (Nature 464:1218 (2010)). Our results demonstrate that, across a wide range of low-resolution structures, significant improvements were achieved in terms of multiple refinement criteria, such as the Rfree value, overfitting and Ramachandran statistics etc.


Chong Zhang

Student in Computational Applied Physics, Rice Quantum Institute/Applied Physics Program
Graduated in Dec. 2013 with a Ph.D. in Computational Applied Physics. Passionate about integrating high performance computing, physics and mathematics to tackle industrial challenges in science and engineering.

Thursday March 6, 2014 4:30pm - 6:30pm PST
BRC Exhibit Hall Rice University 6500 Main Street at University, Houston, TX 77030