This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.We are developing machine learning methods for predicting the quality of a predicted protein structure, measured by its closeness to the native structure, without knowing the native structure. The core of the project is the development of a composite score from a large variety of structural features using support vector regression. This score can then be used to discriminate between good and bad predicted models. Our score has superior discriminative performance in our two test data sets.
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