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Xinqi Gong

Showing results (1-10 of 61) with videos related to

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BMC Bioinformatics|February 18, 2025
Harnessing pre-trained models for accurate prediction of protein-ligand binding affinityJiashan Li, Xinqi Gong
BMC Bioinformatics|November 29, 2019
Attention mechanism enhanced LSTM with residual architecture and its application for protein-protein interaction residue pairs predictionJiale Liu, Xinqi Gong
Biochimica Et Biophysica Acta. Proteins and Proteomics|July 28, 2020
Tetramer protein complex interface residue pairs prediction with LSTM combined with graph representationsDaiwen Sun, Xinqi Gong
Molecules (Basel, Switzerland)|September 26, 2020
A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein TrimersYanfen Lyu, Xinqi Gong
Journal of Theoretical Biology|October 4, 2017
A new probability method to understand protein-protein interface formation mechanism at amino acid levelYongxiao Yang, Xinqi Gong
IEEE/ACM Transactions on Computational Biology and Bioinformatics|May 26, 2017
Protein-Protein Interaction Interface Residue Pair Prediction Based on Deep Learning ArchitectureZhenni Zhao, Xinqi Gong
Plos Computational Biology|May 6, 2026
scHG: A supercell framework with high-order graph learning enables scalable multi-omics analysisYixiang Huang, Yuan Gan, Xinqi Gong
Interdisciplinary Sciences, Computational Life Sciences|March 19, 2020
A Novel Index of Contact Frequency from Noise Protein-Protein Interaction Data Help for Accurate Interface Residue Pair PredictionYanfen Lyu, He Huang, Xinqi Gong
BMC Bioinformatics|April 25, 2020
Heterogeneous multiple kernel learning for breast cancer outcome evaluationXingheng Yu, Xinqi Gong, Hao Jiang
Scientific Reports|November 24, 2017
Different protein-protein interface patterns predicted by different machine learning methodsWei Wang, Yongxiao Yang, Jianxin Yin, et al.
Pageof 7

Showing results (1-10 of 61) with videos related to

Sort By:
Pageof 7
BMC Bioinformatics|February 18, 2025
Harnessing pre-trained models for accurate prediction of protein-ligand binding affinityJiashan Li, Xinqi Gong
BMC Bioinformatics|November 29, 2019
Attention mechanism enhanced LSTM with residual architecture and its application for protein-protein interaction residue pairs predictionJiale Liu, Xinqi Gong
Biochimica Et Biophysica Acta. Proteins and Proteomics|July 28, 2020
Tetramer protein complex interface residue pairs prediction with LSTM combined with graph representationsDaiwen Sun, Xinqi Gong
Molecules (Basel, Switzerland)|September 26, 2020
A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein TrimersYanfen Lyu, Xinqi Gong
Journal of Theoretical Biology|October 4, 2017
A new probability method to understand protein-protein interface formation mechanism at amino acid levelYongxiao Yang, Xinqi Gong
IEEE/ACM Transactions on Computational Biology and Bioinformatics|May 26, 2017
Protein-Protein Interaction Interface Residue Pair Prediction Based on Deep Learning ArchitectureZhenni Zhao, Xinqi Gong
Plos Computational Biology|May 6, 2026
scHG: A supercell framework with high-order graph learning enables scalable multi-omics analysisYixiang Huang, Yuan Gan, Xinqi Gong
Interdisciplinary Sciences, Computational Life Sciences|March 19, 2020
A Novel Index of Contact Frequency from Noise Protein-Protein Interaction Data Help for Accurate Interface Residue Pair PredictionYanfen Lyu, He Huang, Xinqi Gong
BMC Bioinformatics|April 25, 2020
Heterogeneous multiple kernel learning for breast cancer outcome evaluationXingheng Yu, Xinqi Gong, Hao Jiang
Scientific Reports|November 24, 2017
Different protein-protein interface patterns predicted by different machine learning methodsWei Wang, Yongxiao Yang, Jianxin Yin, et al.
Pageof 7