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#1 2024 11

miCGR: interpretable deep neural network for predicting both site-level and gene-level functional targets of microRNA

作者: Xiaolong Wu, Lehan Zhang, Xiaochu Tong, Yitian Wang, Zimei Zhang, Xiangtai Kong, Shengkun Ni, Xiaomin Luo, Mingyue Zheng, Yun Tang, Xutong Li

期刊: Briefings in bioinformatics

信息: 2024 | 26(1) | bbae616

#2 2024 11

ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information

作者: Qiule Yu, Zhixing Zhang, Guixia Liu, Weihua Li, Yun Tang*

期刊: Briefings in Bioinformatics

信息: 2024 | 25(6) | bbae583

#3 2024 10

NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods

作者: Fei Pan, Cheng-Nuo Wang, Zhuo-Hang Yu, Zeng-Rui Wu, Ze Wang, Shang Lou, Wei-Hua Li, Gui-Xia Liu, Ting Li, Yu-Zheng Zhao, Yun Tang

期刊: Acta pharmacologica Sinica

信息: 2024 | 45(10) | 2199-2211

#4 2024 10

In Silico Prediction of ERRα Agonists Based on Combined Features and Stacking Ensemble Method

作者: Jiahao Xu, Zejun Huang, Hao Duan, Weihua Li, Jingyan Zhuang, Le Xiong, Yun Tang, Guixia Liu

期刊: ChemMedChem

信息: 2024 | 19(20) | e202400298

#5 2024 09

Prediction of Cytochrome P450 Substrates Using the Explainable Multitask Deep Learning Models

作者: Jiaojiao Fang, Yan Tang, Changda Gong, Zejun Huang, Yanjun Feng, Guixia Liu, Yun Tang, Weihua Li

期刊: Chemical research in toxicology

信息: 2024 | 37(9) | 1535-1548

#6 2024 07

Evaluation of machine learning models for cytochrome P450 3A4, 2D6, and 2C9 inhibition

作者: Changda Gong, Yanjun Feng, Jieyu Zhu, Guixia Liu, Yun Tang, Weihua Li

期刊: Journal of applied toxicology : JAT

信息: 2024 | 44(7) | 1050-1066

#7 2024 07

admetSAR3.0: a comprehensive platform for exploration, prediction and optimization of chemical ADMET properties

作者: Yaxin Gu, Zhuohang Yu, Yimeng Wang, Long Chen, Chaofeng Lou, Chen Yang, Weihua Li, Guixia Liu, Yun Tang

期刊: Nucleic acids research

信息: 2024 | 52(W1) | W432-W438

#8 2024 07

MetaPredictor: in silico prediction of drug metabolites based on deep language models with prompt engineering

作者: Keyun Zhu, Mengting Huang, Yimeng Wang, Yaxin Gu, Weihua Li, Guixia Liu, Yun Tang

期刊: Briefings in bioinformatics

信息: 2024 | 25(5) | bbae374

#9 2024 06

In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches

作者: Yiqing Zhou, Ze Wang, Zejun Huang, Weihua Li, Yuanting Chen, Xinxin Yu, Yun Tang, Guixia Liu

期刊: Journal of applied toxicology : JAT

信息: 2024 | 44(6) | 892-907

#10 2024 06

In Silico Prediction of Skin Sensitization for Compounds via Flexible Evidence Combination Based on Machine Learning and Dempster-Shafer Theory

作者: Haoqiang Wang, Zejun Huang, Shang Lou, Weihua Li, Guixia Liu, Yun Tang

期刊: Chemical research in toxicology

信息: 2024 | 37(6) | 894-909

#11 2024 06

人工智能在抗癌肽研发中的应用与挑战

作者: Zhixing Zhang, Hua Deng, Yun Tang

期刊: 中国药科大学学报

信息: 2024 | Vol.55（3） | 347 − 356

#12 2024 04

Unraveling the Ligand-Binding Sites of CYP3A4 by Molecular Dynamics Simulations with Solvent Probes

作者: Yanjun Feng, Changda Gong, Jieyu Zhu, Guixia Liu, Yun Tang, Weihua Li

期刊: Journal of chemical information and modeling

信息: 2024 | 64(8) | 3451-3464

#13 2024 03

In Silico prediction of inhibitors for multiple transporters via machine learning methods

作者: Hao Duan, Chaofeng Lou, Yaxin Gu, Yimeng Wang, Weihua Li, Guixia Liu, Yun Tang

期刊: Molecular informatics

信息: 2024 | 43(3) | e202300270

#14 2024 03

In Silico Prediction of Chemical Acute Dermal Toxicity Using Explainable Machine Learning Methods

作者: Shang Lou, Zhuohang Yu, Zejun Huang, Haoqiang Wang, Fei Pan, Weihua Li, Guixia Liu, Yun Tang

期刊: Chemical research in toxicology

信息: 2024 | 37(3) | 513-524

#15 2024 03

MedChatZH: A tuning LLM for traditional Chinese medicine consultations

作者: Yang Tan, Zhixing Zhang, Mingchen Li, Fei Pan, Hao Duan, Zijie Huang, Hua Deng, Zhuohang Yu, Chen Yang, Guoyang Shen, Peng Qi, Chengyuan Yue, Yuxian Liu, Liang Hong, Huiqun Yu, Guisheng Fan, Yun Tang

期刊: Computers in Biology and Medicine

信息: 2024 | Vol.172 | 108290

#16 2024 02

AptaDB: a comprehensive database integrating aptamer-target interactions

作者: Long Chen, Zhuohang Yu, Zengrui Wu, Moran Zhou, Yimeng Wang, Xinxin Yu, Weihua Li, Guixia Liu, Yun Tang

期刊: RNA (New York, N.Y.)

信息: 2024 | 30(3) | 189-199

#17 2024 02

AttentiveSkin: To Predict Skin Corrosion/Irritation Potentials of Chemicals via Explainable Machine Learning Methods

作者: Zejun Huang, Shang Lou, Haoqiang Wang, Weihua Li, Guixia Liu, Yun Tang

期刊: Chemical research in toxicology

信息: 2024 | 37(2) | 361-373

#18 2024 01

XGraphCDS: An explainable deep learning model for predicting drug sensitivity from gene pathways and chemical structures

作者: Yimeng Wang, Xinxin Yu, Yaxin Gu, Weihua Li, Keyun Zhu, Long Chen, Yun Tang, Guixia Liu

期刊: Computers in biology and medicine

信息: 2024 | Vol.168 | 107746

#19 2024 01

mtADENet: A novel interpretable method integrating multiple types of network-based inference approaches for prediction of adverse drug events

作者: Zhuohang Yu, Zengrui Wu, Moran Zhou, Long Chen, Weihua Li, Guixia Liu, Yun Tang

期刊: Computers in biology and medicine

信息: 2024 | Vol.168 | 107831

#20 2024 01

DBPP-Predictor: a novel strategy for prediction of chemical drug-likeness based on property profiles

作者: Yaxin Gu, Yimeng Wang, Keyun Zhu, Weihua Li, Guixia Liu, Yun Tang

期刊: Journal of cheminformatics

信息: 2024 | 16(1) | 4

#21 2024 01

Network-Based Methods and Their Applications in Drug Discovery

作者: Zhuohang Yu, Zengrui Wu, Ze Wang, Yimeng Wang, Moran Zhou, Weihua Li, Guixia Liu, Yun Tang

期刊: Journal of chemical information and modeling

信息: 2024 | 64(1) | 57-75

#22 2024

Uncovering the Oxidative Stress Mechanisms and Targets in Alzheimer's Disease by Integrating Phenotypic Screening Data and Polypharmacology Networks

作者: Moran Zhou, Qian Jiao, Zengrui Wu, Weihua Li, Guixia Liu, Rui Wang, Yun Tang

期刊: Journal of Alzheimer's disease : JAD

信息: 2024 | 99(s1) | S139-S156

发表论文

2024

miCGR: interpretable deep neural network for predicting both site-level and gene-level functional targets of microRNA

ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information

NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods

In Silico Prediction of ERRα Agonists Based on Combined Features and Stacking Ensemble Method

Prediction of Cytochrome P450 Substrates Using the Explainable Multitask Deep Learning Models

Evaluation of machine learning models for cytochrome P450 3A4, 2D6, and 2C9 inhibition

admetSAR3.0: a comprehensive platform for exploration, prediction and optimization of chemical ADMET properties

MetaPredictor: in silico prediction of drug metabolites based on deep language models with prompt engineering

In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches

In Silico Prediction of Skin Sensitization for Compounds via Flexible Evidence Combination Based on Machine Learning and Dempster-Shafer Theory

人工智能在抗癌肽研发中的应用与挑战

Unraveling the Ligand-Binding Sites of CYP3A4 by Molecular Dynamics Simulations with Solvent Probes

In Silico prediction of inhibitors for multiple transporters via machine learning methods

In Silico Prediction of Chemical Acute Dermal Toxicity Using Explainable Machine Learning Methods

MedChatZH: A tuning LLM for traditional Chinese medicine consultations

AptaDB: a comprehensive database integrating aptamer-target interactions

AttentiveSkin: To Predict Skin Corrosion/Irritation Potentials of Chemicals via Explainable Machine Learning Methods

XGraphCDS: An explainable deep learning model for predicting drug sensitivity from gene pathways and chemical structures

mtADENet: A novel interpretable method integrating multiple types of network-based inference approaches for prediction of adverse drug events

DBPP-Predictor: a novel strategy for prediction of chemical drug-likeness based on property profiles

Network-Based Methods and Their Applications in Drug Discovery

Uncovering the Oxidative Stress Mechanisms and Targets in Alzheimer's Disease by Integrating Phenotypic Screening Data and Polypharmacology Networks

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