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Ji-Yong An

Showing results (1-10 of 15) with videos related to

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Biodata Mining|January 21, 2021
An efficient computational method for predicting drug-target interactions using weighted extreme learning machine and speed up robot featuresJi-Yong An, Fan-Rong Meng, Zi-Ji Yan
Evolutionary Bioinformatics Online|October 28, 2024
An Effective Computational Method for Predicting Self-Interacting Proteins Based on VGGNet Convolutional Neural Network and Gray-Level Co-occurrence MatrixDan-Hua Chu, Ji-Yong An, Xiao-Mei Nie
Evolutionary Bioinformatics Online|May 14, 2019
Sequence-based Prediction of Protein-Protein Interactions Using Gray Wolf Optimizer-Based Relevance Vector MachineJi-Yong An, Zhu-Hong You, Yong Zhou, et al.
Evolutionary Bioinformatics Online|October 18, 2019
An Efficient Feature Extraction Technique Based on Local Coding PSSM and Multifeatures Fusion for Predicting Protein-Protein InteractionsJi-Yong An, Yong Zhou, Yu-Jun Zhao, et al.
Evolutionary Bioinformatics Online|June 20, 2020
Predicting Self-Interacting Proteins Using a Recurrent Neural Network and Protein Evolutionary InformationJi-Yong An, Yong Zhou, Zi-Ji Yan, et al.
Journal of Theoretical Biology|August 14, 2017
Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAACJing-Xuan Zhai, Tian-Jie Cao, Ji-Yong An, et al.
Molecules (Basel, Switzerland)|July 6, 2017
Prediction of Drug-Target Interaction Networks from the Integration of Protein Sequences and Drug Chemical StructuresFan-Rong Meng, Zhu-Hong You, Xing Chen, et al.
Journal of Cheminformatics|November 1, 2017
Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary informationJi-Yong An, Lei Zhang, Yong Zhou, et al.
International Journal of Molecular Sciences|May 24, 2016
RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein SequencesJi-Yong An, Zhu-Hong You, Fan-Rong Meng, et al.
International Journal of Molecular Sciences|March 30, 2018
PCLPred: A Bioinformatics Method for Predicting Protein-Protein Interactions by Combining Relevance Vector Machine Model with Low-Rank Matrix ApproximationLi-Ping Li, Yan-Bin Wang, Zhu-Hong You, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Biodata Mining|January 21, 2021
An efficient computational method for predicting drug-target interactions using weighted extreme learning machine and speed up robot featuresJi-Yong An, Fan-Rong Meng, Zi-Ji Yan
Evolutionary Bioinformatics Online|October 28, 2024
An Effective Computational Method for Predicting Self-Interacting Proteins Based on VGGNet Convolutional Neural Network and Gray-Level Co-occurrence MatrixDan-Hua Chu, Ji-Yong An, Xiao-Mei Nie
Evolutionary Bioinformatics Online|May 14, 2019
Sequence-based Prediction of Protein-Protein Interactions Using Gray Wolf Optimizer-Based Relevance Vector MachineJi-Yong An, Zhu-Hong You, Yong Zhou, et al.
Evolutionary Bioinformatics Online|October 18, 2019
An Efficient Feature Extraction Technique Based on Local Coding PSSM and Multifeatures Fusion for Predicting Protein-Protein InteractionsJi-Yong An, Yong Zhou, Yu-Jun Zhao, et al.
Evolutionary Bioinformatics Online|June 20, 2020
Predicting Self-Interacting Proteins Using a Recurrent Neural Network and Protein Evolutionary InformationJi-Yong An, Yong Zhou, Zi-Ji Yan, et al.
Journal of Theoretical Biology|August 14, 2017
Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAACJing-Xuan Zhai, Tian-Jie Cao, Ji-Yong An, et al.
Molecules (Basel, Switzerland)|July 6, 2017
Prediction of Drug-Target Interaction Networks from the Integration of Protein Sequences and Drug Chemical StructuresFan-Rong Meng, Zhu-Hong You, Xing Chen, et al.
Journal of Cheminformatics|November 1, 2017
Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary informationJi-Yong An, Lei Zhang, Yong Zhou, et al.
International Journal of Molecular Sciences|May 24, 2016
RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein SequencesJi-Yong An, Zhu-Hong You, Fan-Rong Meng, et al.
International Journal of Molecular Sciences|March 30, 2018
PCLPred: A Bioinformatics Method for Predicting Protein-Protein Interactions by Combining Relevance Vector Machine Model with Low-Rank Matrix ApproximationLi-Ping Li, Yan-Bin Wang, Zhu-Hong You, et al.
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