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Yanyi Chu

Showing results (11-20 of 21) with videos related to

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Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|November 7, 2025
A Biologically Informed Vision-Guided Framework for Interpretable T Cell Receptor-Epitope Binding PredictionYajing Yuan, Junwei Chen, Yufang Zhang, et al.
Briefings in Bioinformatics|December 31, 2019
DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid featuresYanyi Chu, Aman Chandra Kaushik, Xiangeng Wang, et al.
International Journal of Pharmaceutics|February 22, 2026
Multimodal framework for early developability assessment to accelerate protein and antibody developmentJiayin Deng, Qiong Huang, Jiayi Lv, et al.
Journal of Chemical Theory and Computation|May 30, 2024
Exploring the Conformational Ensembles of Protein-Protein Complex with Transformer-Based Generative ModelJianmin Wang, Xun Wang, Yanyi Chu, et al.
Briefings in Bioinformatics|July 13, 2022
De novo molecular design with deep molecular generative models for PPI inhibitorsJianmin Wang, Yanyi Chu, Jiashun Mao, et al.
Protein Science : a Publication of the Protein Society|November 20, 2023
TEPCAM: Prediction of T-cell receptor-epitope binding specificity via interpretable deep learningJunwei Chen, Bowen Zhao, Shenggeng Lin, et al.
Briefings in Bioinformatics|October 21, 2021
MDF-SA-DDI: predicting drug-drug interaction events based on multi-source drug fusion, multi-source feature fusion and transformer self-attention mechanismShenggeng Lin, Yanjing Wang, Lingfeng Zhang, et al.
Briefings in Bioinformatics|May 19, 2021
MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graphYanyi Chu, Xuhong Wang, Qiuying Dai, et al.
Briefings in Bioinformatics|August 16, 2021
NeuroPpred-Fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methodsMingming Jiang, Bowen Zhao, Shenggan Luo, et al.
Interdisciplinary Sciences, Computational Life Sciences|May 29, 2023
A Self-attention Graph Convolutional Network for Precision Multi-tumor Early Diagnostics with DNA Methylation DataXue Jiang, Zhiqi Li, Aamir Mehmood, et al.
Pageof 3

Showing results (11-20 of 21) with videos related to

Sort By:
Pageof 3
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|November 7, 2025
A Biologically Informed Vision-Guided Framework for Interpretable T Cell Receptor-Epitope Binding PredictionYajing Yuan, Junwei Chen, Yufang Zhang, et al.
Briefings in Bioinformatics|December 31, 2019
DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid featuresYanyi Chu, Aman Chandra Kaushik, Xiangeng Wang, et al.
International Journal of Pharmaceutics|February 22, 2026
Multimodal framework for early developability assessment to accelerate protein and antibody developmentJiayin Deng, Qiong Huang, Jiayi Lv, et al.
Journal of Chemical Theory and Computation|May 30, 2024
Exploring the Conformational Ensembles of Protein-Protein Complex with Transformer-Based Generative ModelJianmin Wang, Xun Wang, Yanyi Chu, et al.
Briefings in Bioinformatics|July 13, 2022
De novo molecular design with deep molecular generative models for PPI inhibitorsJianmin Wang, Yanyi Chu, Jiashun Mao, et al.
Protein Science : a Publication of the Protein Society|November 20, 2023
TEPCAM: Prediction of T-cell receptor-epitope binding specificity via interpretable deep learningJunwei Chen, Bowen Zhao, Shenggeng Lin, et al.
Briefings in Bioinformatics|October 21, 2021
MDF-SA-DDI: predicting drug-drug interaction events based on multi-source drug fusion, multi-source feature fusion and transformer self-attention mechanismShenggeng Lin, Yanjing Wang, Lingfeng Zhang, et al.
Briefings in Bioinformatics|May 19, 2021
MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graphYanyi Chu, Xuhong Wang, Qiuying Dai, et al.
Briefings in Bioinformatics|August 16, 2021
NeuroPpred-Fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methodsMingming Jiang, Bowen Zhao, Shenggan Luo, et al.
Interdisciplinary Sciences, Computational Life Sciences|May 29, 2023
A Self-attention Graph Convolutional Network for Precision Multi-tumor Early Diagnostics with DNA Methylation DataXue Jiang, Zhiqi Li, Aamir Mehmood, et al.
Pageof 3