赵皓晨

硕士生导师

所在单位:大数据研究院

学历:研究生(博士后)

办公地点:中南大学岳麓山校区逸夫楼214

性别:男

联系方式:zhaohaochen@csu.edu.cn

学位:博士学位

在职信息:在职

毕业院校:中南大学

   

个人简介

赵皓晨,男,计算机应用技术博士(导师:王建新教授),硕士生导师。主持和参与国家自然科学基金多项,在Nature子刊、CCF A类期刊、生物信息学领域权威期刊和会议发表论文40余篇(第一/通信20余篇)。现为湖南省生物信息学会医学生物信息学专委会委员,CCF B类国际会议 BIBM 23-26程序委员会成员,CCF C类国际会议 ISBRA 程序委员会成员多个生物信息学领域权威期刊审稿人。


研究方向:利用人工智能算法解决生物信息学问题

>小分子药物发现

>肽药物识别与功能预测

>药物生物效应属性预测

>药物信息学


硕士招生:每年招收1-2名硕士研究生,本课题组依托良好的科研平台与学术合作基础,具备充足的计算资源和稳定的研究支撑,能够为学生开展科研训练提供完善的条件保障。团队重视学生科研能力、学术视野与长期发展的培养,愿意在科研入门、论文写作、项目参与以及继续深造等方面给予充分支持与具体指导。对于认真投入、踏实努力并取得良好成果的同学,课题组也将给予充分认可与积极激励。课题组注重营造开放、平等、务实的学习科研环境,鼓励独立思考、合作交流与持续积累。欢迎有兴趣、有热情、踏实进取的同学加入。



代表性成果:

2026年

1. A Multi-Modal Feature Fusion Method Enhanced by Dynamic Sample Graphs for Predicting Drug Responses[J]. Big Data Mining and Analytics JCR1区,CCF计算领域高质量期刊T1类

2. MVCASyn: Predicting Synergistic Drug Combinations Based on Multi-View Learning and Cross-Attention Mechanism[J]. Journal of Computer Science and Technology JCR1区, CCF计算领域高质量期刊T1类


2025年

1.  MMFF-DDI: a Multi-Modal Fusion Framework for Drug-Drug Interaction Event Prediction with Contrastive Learning[J]. IEEE Transactions on Computational Biology and Bioinformatics (JCR1区, CCF B类期刊

2. MRLF-DDI: A Multi-view Representation Learning Framework for Drug-Drug Interaction Event Prediction[J]. IEEE Journal of Biomedical and Health Informatics (JCR1区, CCF C类期刊

3. ColdstartCPI: Induced-fit theory-guided DTI predictive model with improved generalization performance[J]. Nature Communications JCR1区, Nature Portfolio

4. Probiotic–Disease Association Prediction via Cross-Modal Feature Aggregation[J]. IEEE Transactions on Computational Biology and Bioinformatics JCR1区, CCF B类期刊

5. A deep learning-based method for predicting the frequency classes of drug side effects based on multi-source similarity fusion[J]. Bioinformatics JCR1区, CCF A类期刊

6. AGPred: An End-to-End Deep Learning Model for Predicting Drug Approvals in Clinical Trials Based on Molecular Features[J]. IEEE Journal of Biomedical and Health Informatics (JCR1区, CCF C类期刊

7. MPEMDA: A Multi-Similarity Integration Approach with Pre-completion and Error Correction for Predicting Microbe-Drug Associations[J]. Methods (JCR1区)

8. Predicting thermodynamic stability of inorganic compounds using ensemble machine learning based on electron configuration[J]. Nature Communications  JCR1区, Nature Portfolio


2024年

1. ISGDRP: a multi-modal learning method for drug response prediction[C]. 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (Best paper, SIGBio旗舰会议)

2. Application of machine learning in drug side effect prediction: databases, methods, and challenges[J]. Frontiers of Computer Science (JCR1区, CCF计算领域高质量期刊T1类)

3. BANDRP: a bilinear attention network for anti-cancer drug response prediction based on fingerprint and multi-omics[J]. Briefings in Bioinformatics (JCR1区, CCF B类期刊)

4. A Knowledge Graph-Based Method for Drug-Drug Interaction Prediction With Contrastive Learning[J]. IEEE Transactions on Computational Biology and Bioinformatics (JCR1区, CCF B类期刊)

5. DVMPDC: A Deep Learning Model Based on Dual-View Representation and Multi-Strategy Pooling for Predicting Synergistic Drug Combinations[C]. International Symposium on Bioinformatics Research and Applications(ISBRA)(CCF C类会议)

6. MA-PEP: A novel anticancer peptide prediction framework with multimodal feature fusion based on attention mechanism. Protein Science (JCR 1区)


2023年

1. SCN-MLTPP: A Multi-Label Classifier for Predicting Therapeutic Properties of Peptides Using the Stacked Capsule Network[J]. IEEE Transactions on Computational Biology and Bioinformatics (JCR1区, CCF B类期刊)

2. Identifying the serious clinical outcomes of adverse reactions to drugs by a multi-task deep learning framework[J]. Communications Biology (JCR1区, Nature Portfolio

3. MSDRP: a deep learning model based on multisource data for predicting drug response[J]. Bioinformatics (JCR1区, CCF A类期刊

4. DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing[J]. Nature Communications(JCR1区,Nature Portfolio


2022年

1. Predicting of microbe-drug associations via a pre-completion-based label propagation algorithm[C]. International Conference on Bioinformatics and Biomedicine (BIBM)(CCF B类会议)

2. GIFDTI: Prediction of Drug-Target Interactions Based on Global Molecular and Intermolecular Interaction Representation Learning[J]. IEEE Transactions on Computational Biology and Bioinformatics (JCR1区, CCFB类期刊)

3. SADeepcry: a deep learning framework for protein crystallization propensity prediction using self-attention and auto-encoder networks[J]. Briefings in Bioinformatics (JCR1区, CCFB类期刊)

4. Drug repositioning based on multi-view learning with matrix completion[J]. Briefings in Bioinformatics (JCR1区, CCFB类期刊)

5. NASMDR: a framework for miRNA-drug resistance prediction using efficient neural architecture search and graph isomorphism networks[J]. Briefings in Bioinformatics (JCR1区, CCFB类期刊)


2021年

1. A similarity-based deep learning approach for determining the frequencies of drug side effects[J]. Briefings in Bioinformatics (JCR1区, CCFB类期刊)

2. HyperAttentionDTI: improving drug–protein interaction prediction by sequence-based deep learning with attention mechanism[J]. Bioinformatics (JCR1区, CCF A类期刊

3. A novel graph attention model for predicting frequencies of drug-side effects from multi-view data[J]. Briefings in Bioinformatics (JCR1区, CCFB类期刊)

4. RNPredATC: A Deep Residual Learning-Based Model With Applications to the Prediction of Drug-ATC Code Association[J]. IEEE Transactions on Computational Biology and Bioinformatics (JCR1区, CCFB类期刊)

5. A Convolutional Neural Network and Graph Convolutional Network Based Method for Predicting the Classification of Anatomical Therapeutic Chemicals[J]. Bioinformatics (JCR1区, CCF A类期刊

6. A novel approach based on deep residual learning to predict drug's anatomical therapeutic chemical code[C]. International Conference on Bioinformatics and Biomedicine (BIBM)(CCF B类会议)


在研项目:

(1)国家自然科学基金,基于多源数据融合与大型语言模型驱动的药物不良反应预测研究,2026-01-01至2028-12-31

(2)国家自然科学基金,面向miRNA靶标的小分子药物辅助设计与筛选研究,2026-01-01至2029-12-31

(3)国家自然科学基金,基于知识迁移的患者个性化抗癌药物敏感性预测方法研究,2025-01-01至2028-12-31


工作经历

[1]   2025.7-至今

中南大学  |  大数据研究院  |  讲师

[2]   2023.7-2025.7

中南大学  |  计算机学院  |  博士后