General Information
| Description | Improved model quality assessments using deep learning |
| Homepage | http://proq3.bioinfo.se/ |
Publications
ProQ3D: improved model quality assessments using deep learning
Summary:
Protein quality assessment is a long-standing problem in bioinformatics. For more than a decade we have developed state-of-art predictors by carefully selecting and optimising inputs to a machine learning method. The correlation has increased from 0.60 in ProQ to 0.81 in ProQ2 and 0.85 in ProQ3 mainly by adding a large set of carefully tuned descriptions of a protein. Here, we show that a substantial improvement can be obtained using exactly the same inputs as in ProQ2 or ProQ3 but replacing the support vector machine by a deep neural network. This improves the Pearson correlation to 0.90 (0.85 using ProQ2 input features).
Availability and Implementation:
ProQ3D is freely available both as a webserver and a stand-alone program at http://proq3.bioinfo.se/
Contact:
arne@bioinfo.se
Supplementary information:
Supplementary data are available at Bioinformatics online.
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