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Extracting knowledge from protein structure geometry
Peter Rogen, Patrice Koehl Department of Computer Science and Genome Center, UC, Davis Proteins 2013 Presented by Chao Wang
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Background Model Energy Knowledge Estimation Generation vs. Evaluation
Physics-based vs. Knowledge-based Knowledge Local vs. Global (Non-local): mean force Estimation RMSD, GDT_TS
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Introduction
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Methods Local Geometry: 7-mer fragments Nonlocal Geometry
Solvent effects Weights training
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Local
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Ignoring Smooth Kernel
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Non-local: A pairwise potential
Ignoring regularization
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Modeling Solvent Effects
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Complete Potential
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Discussion
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Chao’s comments This potential can’t describe the first phase of folding. Hierarchical potential.
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