Predict the Tertiary Structure of Protein with Binary Tree and Ensemble Strategy
Yiming Chen, Yuehui Chen
Available Online April 2013.
- https://doi.org/10.2991/icsem.2013.120How to use a DOI?
- tertiary structure,binary tree, selective ensemble,FNT
- In this paper we intend to apply a new method to predict tertiary structure. Several feature extraction methods adopted are physicochemical composition, recurrence quantification analysis (RQA) , pseudo amino acid composition (PseAA) and Distance frequency. We construct the binary tree Classification model, and adopt flexible neural tree models as the classifiers. We will train a number of based classifiers through different features extraction methods for every node of binary tree, then employ the selective ensemble method to ensemble them. 640 dataset is selected to our experiment. The predict accuracy with our method on this data set is 63.58%, higher than some other methods on the 640 datasets. So, our method is feasible and effective in some extent.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yiming Chen AU - Yuehui Chen PY - 2013/04 DA - 2013/04 TI - Predict the Tertiary Structure of Protein with Binary Tree and Ensemble Strategy BT - 2nd International Conference On Systems Engineering and Modeling (ICSEM-13) PB - Atlantis Press SP - 603 EP - 607 SN - 1951-6851 UR - https://doi.org/10.2991/icsem.2013.120 DO - https://doi.org/10.2991/icsem.2013.120 ID - Chen2013/04 ER -