Karolis Uziela1, David Menéndez Hurtado1, Nanjiang Shu1,2, Björn Wallner3, Arne Elofsson1. 1. Department of Biochemistry and Biophysics and Science for Life Laboratory, Stockholm University, Solna, Sweden. 2. Bioinformatics Short-term Support and Infrastructure (BILS), Science for Life Laboratory, Solna, Sweden. 3. Department of Physics, Chemistry and Biology (IFM)/Bioinformatics. Linköping University, ?Linköping, Sweden.
Abstract
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.
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.
Authors: Jianlin Cheng; Myong-Ho Choe; Arne Elofsson; Kun-Sop Han; Jie Hou; Ali H A Maghrabi; Liam J McGuffin; David Menéndez-Hurtado; Kliment Olechnovič; Torsten Schwede; Gabriel Studer; Karolis Uziela; Česlovas Venclovas; Björn Wallner Journal: Proteins Date: 2019-07-16