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Ping Xuan

Showing results (31-40 of 119) with videos related to

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Biomed Research International|December 8, 2015
Improved Pre-miRNA Classification by Reducing the Effect of Class ImbalanceYingli Zhong, Ping Xuan, Ke Han, et al.
Molecules (Basel, Switzerland)|July 28, 2019
Inferring Drug-Related Diseases Based on Convolutional Neural Network and Gated Recurrent UnitPing Xuan, Lianfeng Zhao, Tiangang Zhang, et al.
Cells|July 25, 2019
Convolutional Neural Network and Bidirectional Long Short-Term Memory-Based Method for Predicting Drug-Disease AssociationsPing Xuan, Yilin Ye, Tiangang Zhang, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|March 17, 2021
Inferring Drug-Target Interactions Based on Random Walk and Convolutional Neural NetworkXiaoqiang Xu, Ping Xuan, Tiangang Zhang, et al.
Briefings in Bioinformatics|February 9, 2022
Learning multi-scale heterogenous network topologies and various pairwise attributes for drug-disease association predictionHongda Zhang, Hui Cui, Tiangang Zhang, et al.
Frontiers in Genetics|May 28, 2019
Dual Convolutional Neural Networks With Attention Mechanisms Based Method for Predicting Disease-Related lncRNA GenesPing Xuan, Yangkun Cao, Tiangang Zhang, et al.
Briefings in Bioinformatics|April 8, 2022
Heterogeneous multi-scale neighbor topologies enhanced drug-disease association predictionPing Xuan, Xiangfeng Meng, Ling Gao, et al.
Briefings in Bioinformatics|April 1, 2022
Fully connected autoencoder and convolutional neural network with attention-based method for inferring disease-related lncRNAsPing Xuan, Zhe Gong, Hui Cui, et al.
Cells|September 5, 2019
Graph Convolutional Network and Convolutional Neural Network Based Method for Predicting lncRNA-Disease AssociationsPing Xuan, Shuxiang Pan, Tiangang Zhang, et al.
IEEE Journal of Biomedical and Health Informatics|November 20, 2020
Graph Convolutional Autoencoder and Fully-Connected Autoencoder with Attention Mechanism Based Method for Predicting Drug-Disease AssociationsPing Xuan, Ling Gao, Nan Sheng, et al.
Pageof 12

Showing results (31-40 of 119) with videos related to

Sort By:
Pageof 12
Biomed Research International|December 8, 2015
Improved Pre-miRNA Classification by Reducing the Effect of Class ImbalanceYingli Zhong, Ping Xuan, Ke Han, et al.
Molecules (Basel, Switzerland)|July 28, 2019
Inferring Drug-Related Diseases Based on Convolutional Neural Network and Gated Recurrent UnitPing Xuan, Lianfeng Zhao, Tiangang Zhang, et al.
Cells|July 25, 2019
Convolutional Neural Network and Bidirectional Long Short-Term Memory-Based Method for Predicting Drug-Disease AssociationsPing Xuan, Yilin Ye, Tiangang Zhang, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|March 17, 2021
Inferring Drug-Target Interactions Based on Random Walk and Convolutional Neural NetworkXiaoqiang Xu, Ping Xuan, Tiangang Zhang, et al.
Briefings in Bioinformatics|February 9, 2022
Learning multi-scale heterogenous network topologies and various pairwise attributes for drug-disease association predictionHongda Zhang, Hui Cui, Tiangang Zhang, et al.
Frontiers in Genetics|May 28, 2019
Dual Convolutional Neural Networks With Attention Mechanisms Based Method for Predicting Disease-Related lncRNA GenesPing Xuan, Yangkun Cao, Tiangang Zhang, et al.
Briefings in Bioinformatics|April 8, 2022
Heterogeneous multi-scale neighbor topologies enhanced drug-disease association predictionPing Xuan, Xiangfeng Meng, Ling Gao, et al.
Briefings in Bioinformatics|April 1, 2022
Fully connected autoencoder and convolutional neural network with attention-based method for inferring disease-related lncRNAsPing Xuan, Zhe Gong, Hui Cui, et al.
Cells|September 5, 2019
Graph Convolutional Network and Convolutional Neural Network Based Method for Predicting lncRNA-Disease AssociationsPing Xuan, Shuxiang Pan, Tiangang Zhang, et al.
IEEE Journal of Biomedical and Health Informatics|November 20, 2020
Graph Convolutional Autoencoder and Fully-Connected Autoencoder with Attention Mechanism Based Method for Predicting Drug-Disease AssociationsPing Xuan, Ling Gao, Nan Sheng, et al.
Pageof 12