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Sorting protein decoys by machine-learning-to-rank 期刊论文

编号：

f45615ae-3be2-4661-9c2e-a73ee2ca6af1
作者：

Jing, Xiaoyang^[1] Wang, Kai^[2] Lu, Ruqian^[1] Dong, Qiwen^[3]
语种：

英文
期刊：

SCIENTIFIC REPORTS ISSN：2045-2322 2016 年 6 卷 ; AUG 17
收录：
摘要：

Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, and these methods could be roughly divided into three categories: the single-model methods, clustering-based methods and quasi single-model methods. In this study, we develop a single-model method MQAPRank based on the learning-to-rank algorithm firstly, and then implement a quasi single-model method Quasi-MQAPRank. The proposed methods are benchmarked on the 3DRobot and CASP11 dataset. The five-fold cross-validation on the 3DRobot dataset shows the proposed single model method outperforms other methods whose outputs are taken as features of the proposed method, and the quasi single-model method can further enhance the performance. On the CASP11 dataset, the proposed methods also perform well compared with other leading methods in corresponding categories. In particular, the Quasi-MQAPRank method achieves a considerable performance on the CASP11 Best150 dataset.
推荐引用方式
GB/T 7714：

Jing Xiaoyang,Wang Kai,Lu Ruqian, et al. Sorting protein decoys by machine-learning-to-rank [J].SCIENTIFIC REPORTS,2016,6.
APA：

Jing Xiaoyang,Wang Kai,Lu Ruqian,Dong Qiwen.(2016).Sorting protein decoys by machine-learning-to-rank .SCIENTIFIC REPORTS,6.
MLA：

Jing Xiaoyang, et al. "Sorting protein decoys by machine-learning-to-rank" .SCIENTIFIC REPORTS 6(2016).

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