Jianyu Shi
Orcid: 0000-0002-9573-3893
According to our database1,
Jianyu Shi
authored at least 48 papers
between 2006 and 2024.
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Bibliography
2024
Comprehensive Review of Drug-Drug Interaction Prediction Based on Machine Learning: Current Status, Challenges, and Opportunities.
J. Chem. Inf. Model., January, 2024
Knowl. Based Syst., 2024
Neurocomputing, 2024
GGI-DDI: Identification for key molecular substructures by granule learning to interpret predicted drug-drug interactions.
Expert Syst. Appl., 2024
Comput. Biol. Medicine, 2024
DVL-CC: A Novel Dual-View Learning Framework for Compound Cocrystal Prediction Boosted by View Consistency and Complementarity.
Proceedings of the 15th ACM International Conference on Bioinformatics, 2024
2023
IEEE Trans. Pattern Anal. Mach. Intell., August, 2023
CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning.
Bioinform., August, 2023
Attention-based cross domain graph neural network for prediction of drug-drug interactions.
Briefings Bioinform., July, 2023
Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction.
Briefings Bioinform., July, 2023
A social theory-enhanced graph representation learning framework for multitask prediction of drug-drug interactions.
Briefings Bioinform., January, 2023
DGANDDI: Double Generative Adversarial Networks for Drug-Drug Interaction Prediction.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
TCM-GPT: Efficient Pre-training of Large Language Models for Domain Adaptation in Traditional Chinese Medicine.
CoRR, 2023
CProMG: controllable protein-oriented molecule generation with desired binding affinity and drug-like properties.
Bioinform., 2023
Bamboo Agents: Exploring the Potentiality of Digital Craft by Decoding and Recoding Process.
Proceedings of the Seventeenth International Conference on Tangible, 2023
MTGL-ADMET: A Novel Multi-task Graph Learning Framework for ADMET Prediction Enhanced by Status-Theory and Maximum Flow.
Proceedings of the Research in Computational Molecular Biology, 2023
GELKcat: An Integration Learning of Substrate Graph with Enzyme Embedding for Kcat prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
2022
Inf. Sci., 2022
BMC Bioinform., 2022
MLGL-MP: a Multi-Label Graph Learning framework enhanced by pathway interdependence for Metabolic Pathway prediction.
Bioinform., 2022
STNN-DDI: a Substructure-aware Tensor Neural Network to predict Drug-Drug Interactions.
Briefings Bioinform., 2022
Drug-drug interaction prediction with learnable size-adaptive molecular substructures.
Briefings Bioinform., 2022
Briefings Bioinform., 2022
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
Quant. Biol., December, 2021
SSI-DDI: substructure-substructure interactions for drug-drug interaction prediction.
Briefings Bioinform., 2021
2020
2019
Detecting drug communities and predicting comprehensive drug-drug interactions via balance regularized semi-nonnegative matrix factorization.
J. Cheminformatics, 2019
Predicting combinative drug pairs via multiple classifier system with positive samples only.
Comput. Methods Programs Biomed., 2019
2018
Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.
BMC Syst. Biol., 2018
BMCMDA: a novel model for predicting human microbe-disease associations via binary matrix completion.
BMC Bioinform., 2018
TMFUF: a triple matrix factorization-based unified framework for predicting comprehensive drug-drug interactions of new drugs.
BMC Bioinform., 2018
2017
Predicting combinative drug pairs towards realistic screening via integrating heterogeneous features.
BMC Bioinform., 2017
Predicting Comprehensive Drug-Drug Interactions for New Drugs via Triple Matrix Factorization.
Proceedings of the Bioinformatics and Biomedical Engineering, 2017
2016
J. Comb. Optim., 2016
Predicting existing targets for new drugs base on strategies for missing interactions.
BMC Bioinform., 2016
LCM-DS: A novel approach of predicting drug-drug interactions for new drugs via Dempster-Shafer theory of evidence.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
2015
Predicting Drug-Target Interactions Between New Drugs and New Targets via Pairwise K-nearest Neighbor and Automatic Similarity Selection.
Proceedings of the Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques, 2015
SRP: A concise non-parametric similarity-rank-based model for predicting drug-target interactions.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015
2014
Proceedings of the Frontiers in Algorithmics - 8th International Workshop, 2014
Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering<sup>1</sup>.
Proceedings of the 2014 IEEE International Conference on Bioinformatics and Biomedicine, 2014
2010
Local Phase Quantization Texture Descriptor for Protein Classification.
Proceedings of the International Conference on Bioinformatics & Computational Biology, 2010
2009
Fast SCOP Classification of Structural Class and Fold Using Secondary Structure Mining in Distance Matrix.
Proceedings of the Pattern Recognition in Bioinformatics, 2009
2008
A new system for computer-aided intraoperative simulation and postoperative facial appearance prediction of orthognathic surgery.
Proceedings of the International Workshop on Multimedia Signal Processing, 2008
2007
Proceedings of the Pattern Recognition in Bioinformatics, 2007
2006
Prediction of Protein Subcellular Localizations Using Moment Descriptors and Support Vector Machine.
Proceedings of the Pattern Recognition in Bioinformatics, International Workshop, 2006