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谢良旭编委: 职称：副研究员; 单位：江苏理工学院; 社会任职：担任Current Topics in Medicinal Chemistry, Journal of Computational Biology, Current Computer-Aided Drug Design, Artificial Intelligence Review等多个国际期刊审稿人。

个人简介

谢良旭,中国计算机学会会员（C8321M）、中国人工智能学会会员（E661018941M）、中国化学会、IEEE会员(99889346)。担任Current Topics in Medicinal Chemistry, Journal of Computational Biology, Current Computer-Aided Drug Design, Artificial Intelligence Review等多个国际期刊审稿人。担任Current Topics in Medicinal Chemistry期刊的栏目编辑（Section Editor）。主持国家自然科学基金青年项目、江苏省自然科学基金等项目，江苏省“双创博士”。获得江苏省高等学校科学技术研究成果奖三等奖2次。已发表论文40余篇，研究工作发表在J. Chem. Phys.，Chem. Eng. J.， Chem. Biol. Drug Des.，Nat. Commun.等专业领域期刊上，先后申请发明专利10项，4项已授权，获得软件著作权3项。

教育经历

▪2012年-2016年，博士, 香港大学
▪2007年-2011年，本科, 山东大学

学术贡献

[1] XIE L, JIN Y, XU L, et al. Fusing Domain Knowledge with a Fine-Tuned Large Language Model for Enhanced Molecular Property Prediction [J]. J Chem Theory Comput, 2025, 21(14): 6743-58.
[2] XIA R, LI W, CHENG Y, et al. Molecular surfaces modeling: Advancements in deep learning for molecular interactions and predictions [J]. Biochemical and Biophysical Research Communications, 2025, 763: 151799.
[3] LU X, XIE L, XU L, et al. Multimodal fused deep learning for drug property prediction: Integrating chemical language and molecular graph [J]. Comput Struct Biotechnol J, 2024, 23: 1666-79.
[4] LI B, WANG Y, YIN Z, et al. Decision tree-based identification of important molecular fragments for protein-ligand binding [J]. Chem Biol Drug Des, 2024, 103(1): e14427.
[5] ZHANG C, XIE L, LU X, et al. Developing an Improved Cycle Architecture for AI-Based Generation of New Structures Aimed at Drug Discovery [J/OL] 2024, 29(7):10.3390/molecules29071499
[6] WANG Z, SHI H, ZHOU L, et al. Research Progress in Tumor Diagnosis Based on Raman Spectroscopy [J]. Curr Med Imaging, 2024, 20.
[7] MAO R, XIE L, LU X, et al. Harnessing Multiple Level Features to Improve Segmentation Performance of Deep Neural Network: A Case Study in Magnetic Resonance Imaging of Nasopharyngeal Cancer [J]. IEEE Access, 2024, 12: 82469-81.
[8] SHI H, WANG Z, ZHOU L, et al. Status and Prospects of Research on Deep Learning-based De Novo Generation of Drug Molecules [J]. Curr Comput Aided Drug Des, 2024.
[9] 胡帅 , 孔韧 , 谢良旭 . 机器学习预测化合物的雌雄激素受体活性 [J]. 现代计算机 , 2023, 29(01): 16-21.
[10] ZHANG Y, XIE L, ZHANG D, et al. Application of Machine Learning Methods to Predict the Air Half-Lives of Persistent Organic Pollutants [J]. Molecules, 2023, 28(22).
[11] ZHANG D W, XIE L, XU X S, et al. A Broad-Spectrum Antiviral Molecule, Protoporphyrin IX, Acts as a Moderator of HIV-1 Capsid Assembly by Targeting the Capsid Hexamer [J]. Microbiol Spectr, 2023, 11(1): e0266322.
[12] YIN Z, SONG W, LI B, et al. Neural networks prediction of the protein-ligand binding affinity with circular fingerprints [J]. Technology and health care : official journal of the European Society for Engineering and Medicine, 2023, 31(S1): 487-95.
[13] WANG F, XIA R, SU Y, et al. Quantifying RNA structures and interactions with a unified reduced chain representation model [J]. Int J Biol Macromol, 2023, 253(Pt 5): 127181.
[14] WANG F, LI W, LI B, et al. cRNAsp12 Web Server for the Prediction of Circular RNA Secondary Structures and Stabilities [J]. Int J Mol Sci, 2023, 24(4).
[15] SUN L, ZHANG M, XIE L, et al. Computational prediction of Lee retention indices of polycyclic aromatic hydrocarbons by using machine learning [J]. Chem Biol Drug Des, 2023, 101(2): 380-94.
[16] SUN L, ZHANG M, XIE L, et al. In silico prediction of boiling point, octanol-water partition coefficient, and retention time index of polycyclic aromatic hydrocarbons through machine learning [J]. Chem Biol Drug Des, 2023, 101(1): 52-68.
[17] PANG M, HE W, LU X, et al. CoDock-Ligand: combined template-based docking and CNN-based scoring in ligand binding prediction [J]. BMC Bioinformatics, 2023, 24(1): 444.
[18] 张莉莉张莉莉, 蒋益锋蒋益锋, 谢良旭谢良旭, et al. 蛋白质分子机器结构的特性分析及去折叠研究蛋白质分子机器结构的特性分析及去折叠研究 [J]. 数据采集与处理数据采集与处理, 2022, 37(05): 1126-33.
[19] 宋伟宋伟, 谢建平谢建平, 高倩高倩, et al. 基于图像插值的小样本手写数字识别研究基于图像插值的小样本手写数字识别研究 [J]. 数据采集与处理数据采集与处理, 2022, 37(02): 298-307.
[20] XU X, JIN L, XIE L, et al. Landscape Zooming toward the Prediction of RNA Cotranscriptional Folding [J]. J Chem Theory Comput, 2022, 18(3): 2002-15.

工作经历

1. 副研究员，江苏理工学院， 2020年-至今

2. 校聘副教授，江苏理工学院，2019年-2020年

3. Research Associate, 香港科技大学化学系, 2017年-2018年

4. Research Assistant, 香港大学化学系, 2016年-2017年

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