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. 2019 Sep 18;7:224. doi: 10.3389/fbioe.2019.00224

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Copyright © 2019 Meng, Jin, Wang, Guo and Zou.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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AOPs-SVM flowchart. The original dataset (positive and negative dataset) is processed in three phases. (A) In the feature extraction phase, two types of profiles are constructed using the PSI-BLAST and PSI-PRED programs. Then, 473D discrete vectors are generated by combining evolutionary information and secondary processing feature information, including 20D PSSM features, 20D 1-g, 400D 2-g features, 6D secondary structure sequence features and 27D global and local structural features. (B) In feature selection phase, ranking the 473D features by MRMD score and selecting optimal feature set by Random Forest. (C) At last, in model generation phase the optimal feature set is fed into SVM to generate the AOPs-SVM model and optimize it via a grid search.