Ling-Feng Zhao

发表

GenCLiP 2.0: a web server for functional clustering of genes and construction of molecular networks based on free terms

Hai Zhang, Pei Lin, Zhong-Xi Huang, 2014, Bioinform..

Modeling DTA by Combining Multiple-Instance Learning with a Private-Public Mechanism

Junjie Wang, Naifeng Wen, Ling-Feng Zhao, 2022, International journal of molecular sciences.

Learning representations for gene ontology terms by jointly encoding graph structure and textual node descriptors

Junjie Wang, Naifeng Wen, Ling-Feng Zhao, 2022, Briefings Bioinform..

GenCLiP 3: mining human genes' functions and regulatory networks from PubMed based on co-occurrences and natural language processing

Zhong-Xi Huang, Kai-Tai Yao, Dan Guo, 2019, Bioinform..

DFFNDDS: prediction of synergistic drug combinations with dual feature fusion networks

Junjie Wang, Yun Liu, Naifeng Wen, 2023, Journal of Cheminformatics.

Reliability modeling and contrastive learning for unsupervised person re-identification

Junjie Wang, Ling-Feng Zhao, Chunyu Wang, 2023, Knowl. Based Syst..

SeqGO-CPA: Improving Compound-Protein Binding Affinity Prediction with Sequence Information and Gene Ontology Knowledge

Naifeng Wen, Yan Zhu, Chunyu Wang, 2021, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Using a stacked ensemble learning framework to predict modulators of protein-protein interactions

Junjie Wang, Mengyao Gao, Ling-Feng Zhao, 2023, Comput. Biol. Medicine.

DataDTA: a multi-feature and dual-interaction aggregation framework for drug–target binding affinity prediction

Junjie Wang, Chunyu Wang, Naifeng Wen, 2023, Bioinformatics.

Continuous Prompt for Chemical Language Model Aided Anticancer Synergistic Drug Combination Prediction

Junjie Wang, Ling-Feng Zhao, Chunyu Wang, 2023, 2023 IEEE International Conference on Big Data (BigData).

PPII-AEAT: Prediction of protein-protein interaction inhibitors based on autoencoders with adversarial training

Junjie Wang, Ling-Feng Zhao, Chunyu Wang, 2024, Comput. Biol. Medicine.