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Fast Geometric Consensus Approach for Protein Model Quality Assessment

This study presents a novel method for assessing protein model quality using a fast geometric consensus approach. It focuses on template selection and individual model assessment as part of the CASP initiative. The authors, led by Jaroslaw Meller from the University of Cincinnati, demonstrate how true Model Quality Assessment (MQA) and consensus MQA can be efficiently defined and calculated, incorporating free energy, internal energy, temperature, and entropy into the evaluation process. The results highlight the importance of advanced methodologies in enhancing selection efficacy.

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Fast Geometric Consensus Approach for Protein Model Quality Assessment

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  1. Fast Geometric Consensus Approach for Protein Model Quality Assessment Jaroslaw Meller, University of Cincinnati College of Medicine Published at Journal of Computational Biology, 2011 Presented by Chao Wang

  2. Motivation & Background • Template selection and Model selection for CASP • True (individual) MQA and Consensus MQA • F=U-TS • F: Free Energy • U: Internal Energy • T: Temprature • S: Entropy • All happy families are alike but unfortunate families each are not identical. --Leo Tolstoy ``Anna Karenina''

  3. Introduction

  4. Methods • How to define • How to calculate • Data sets

  5. Methods

  6. Data sets

  7. Results

  8. Conclusion • ……

  9. Chao's comments • Chao's perspective: • All methods which not distinguishing templates are not efficient. • CLE rather than SS • D-score is higher complexible on the length of structure • Merge true QA and consensus QA in our SVM • Effect from templates

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