纪宏超课题组

纪宏超

ji.hongchao@foxmail.com

简历介绍

纪宏超，研究员，博士生导师，课题组长。

长期致力于计算机科学与化学生物学的交叉研究。以生物信息学为主要手段，开发一系列用于植物、作物代谢组学数据分析的新算法、新技术，并围绕“未知小分子结构与功能预测”这一核心科学问题展开研究工作。获得国家自然科学基金2项、深圳市优秀科技人才培养项目等，在Nature Communications、Cell Chemical Biology、Analytical Chemistry、Briefings in Bioinformatics等国际学术期刊上发表论文20余篇。申请国家发明专利2项，PCT国际专利1项。担任Briefings in Bioinformatics, Journal of Chemical Information and Modeling, Analytical and Bioanalytical Chemistry, Chemometrics and Intelligent Laboratory Systems，Computers in Biology and Medicine等期刊审稿人，Metabolites期刊客座编辑。

工作经历

2024.09 – 至今        中国农科院深圳农业基因组研究所    研究员

2022.06 – 2024.08  中国农科院深圳农业基因组研究所    副研究员

2020.05 – 2022.06  南方科技大学                                  博士后

教育经历

2015.09 - 2020.06 中南大学 化学化工学院 理学博士

2011.09 - 2015.07 中南大学 化学化工学院 工学学士

研究方向

1）化学信息学与人工智能算法开发及其在植物代谢组学的应用

2）植物、作物代谢组学质谱数据解析算法与软件开发

3）植物、作物中未知小分子代谢物结构注释与功能解析

团队招聘

常年招访问学者、博士后、客座研究生和科研助理，欢迎对高分辨质谱数据解析及代谢组学生物信息学分析方法和基于深度学习的未知小分子化合物结构与功能预测研究方向感兴趣的优秀科研人员和同学申请。

欢迎各高校和研究单位同学来本课题组实习，欢迎报考本实验室博士和硕士研究生。

代表论著（近5年）：

2026

(1) Jiang S.; Yang Q.; Xiong Z.; Li K.; Dai Q.; Su M.; Lyu Y.; Peng Y.; Du R.; Yan J.; Ji H.*. DeepMASS v2: An enhanced deep learning platform for large-scale discovery and structural annotation of unknown plant metabolites. Plant Communications. 2026, 101976,2590-3462.

(2) Liu W.; Zheng Z.; Wang X.; Ji H.*. FiLM-Enhanced Biologically Informed Neural Networks for Multiclass Omics Analysis and Biomarker Discovery. Anal. Chem. 2026, 98(17):12851-12861.

(3) Wang Q.; Yu N.; Song Y.; Fan X.; Tian J.; Chang S.; Guo Y.; Tan C.S.H.; Ji H.*. Thermal Proteomics and AI-assisted Target Deconvolution Identify ACLY as a Direct Target of Demethylzeylasteral in Psoriasis. Anal. Chem. 2026.

(4) Xiong, Z., Wang, X., Liu, J., Cong, S., Yang, Q., & Ji, H.*. Unified Multitask Modeling for Retention Time Prediction Across Chromatographic Conditions. Analytical Chemistry, 2026,98(13), 9500–9507.

(5) Fan, X., Li, Z., Shang, L., Zhang, J., Liu, B., Ren, X., Liu, G., Li, X., Yang, T., & Ji, H.*. DeepHSI: A transferable and expandable hyperspectral framework for industrial plant origin identification: A case study of Pogostemon cablin (Blanco) Benth. Talanta. 2026,303, 129474.

2025

(6) Fan, X., Liu, Y., Zhang, Z., Zhao, P., Li, Z., Zhou, J., Zhai, D., Hu, Y., Li, P., & Ji, H.* DeepPHSI: attention-driven CNN-LSTM fusion for hyperspectral origin traceability across Pogostemon cablin batches. RSC Advances.2025,15(44), 37039–37049.

(7) Fan, X., Shang, L., Zhao, S., Fan, J., Zhang, S., Yang, Q., Wu, C., Liu, Y., Yang, T., & Ji, H.* PLSELM: A lightweight modeling approach for low-data calibration in near-infrared spectroscopy. Analytica Chimica Acta.2025, 1379, 344728.

(8) Fan, X., Gao, L., Lv, J., Li, B., Xu, K., Li, X., Shao, Y., Yang, T., Chen, X., & Ji, H.* A systematic calibration transfer and quantification method based on principal components extreme learning machine for near-infrared spectroscopy. Analytica Chimica Acta, 2025,1361, 344151.

(9) Chen, Y., Zeng, H., Song, Y., Li, Z., Chu, G., Tian, J., & Ji, H.* Development of StatMS platform coupled with MS metabolomics identifies altitude-responsive metabolites in Coreopsis tinctoria Nutt․. Chinese Journal of Analytical Chemistry.2025,53(9), 100569.

(10) Song, Y., Zhang, M., Chang, S., Chu, G., & Ji, H. DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products. Molecules.2025, 30(8), 1683.

(11) Cong, S., Zhang, M., Song, Y., Chang, S., Tian, J., Zeng, H., & Ji, H.* (2025). Graph-sequence enhanced transformer for template-free prediction of natural product biosynthesis. Patterns.2025, 6(8), 101259.

2024

(12) Chen J.; Yang Q.; Dai Q.; Chang S.; Tian J.; Cong S*; Ji, H.*. FederEI: Federated Library Matching Framework for Electron Ionization Mass Spectrum Based Compound Identification. Analytical Chemistry,2024,96(40), 15840–15845.

(13) Li, H.; Fotouhi, N.; Liu, F.; Ji, H.;* Wu, Q.* Early detection of dark-affected plant mechanical responses using enhanced electrical signals. Plant Methods. 2024, 22 (1) 49.

2022-2023:

(14) Ji, H.#; Lu, X.#; Zhao, S.; Wang, Q.; Bin, L.; Huber, K. V. M.; Luo, R.; Tian, R.; Tan, C. S. H. Target deconvolution with matrix-augmented pooling strategy reveals cell-specific drug-protein interactions. Cell Chem. Biol. 2023, 30(11) 1478-1487. (Cell子刊)

(15) Yang, Q.#; Ji, H.#; Xu, Z.; Li, Y.; Wang, P.; Sun, J.; Fan, X.; Zhang, H.; Lu, H.; Zhang, Z. Ultra-Fast and Accurate Electron Ionization Mass Spectrum Matching for Compound Identification with Million-Scale in-Silico Library. Nat. Commun. 2023, 14 (1), 3722. (Nature子刊, Nature Index期刊)

(16) Song, Y., Chang, S., Tian, J., Pan, W., Feng.,* Ji, H.,* A Comprehensive Comparative Analysis of Deep Learning Based Feature Representations for Molecular Taste Prediction. Foods. 2023, 12(18), 3386.

(17) Ji, H.*; Tian, J. Deep Denoising Autoencoder-Assisted Continuous Scoring of Peak Quality in High-Resolution LC−MS Data. Chemo. Intell. Lab. 2022, 231, 104694.

(18) Ji, H.; Lu, X.; Zheng, Z.; Sun, S.; Tan, C.S.H. ProSAP: A GUI Software Tool for Statistical Analysis and Assessment of Thermal Stability Data. Brief. Bioinform. 2022, 23 (3), bbac057.

2014 - 2021

(19) Ji, H.; Deng, H.; Lu, H.; Zhang, Z. Predicting a Molecular Fingerprint from an Electron Ionization Mass Spectrum with Deep Neural Networks. Anal. Chem. 2020, 92 (13), 8649–8653. (Nature Index期刊)

(20) Ji, H.; Zhang, Z.; Lu, H. TarMet: A Reactive GUI Tool for Efficient and Confident Quantification of MS Based Targeted Metabolic and Stable Isotope Tracer Analysis. Metabolomics 2018, 14 (5), 68.

(21) Ji, H.; Zeng, F.; Xu, Y.; Lu, H.; Zhang, Z. KPIC2: An Effective Framework for Mass Spectrometry-Based Metabolomics Using Pure Ion Chromatograms. Anal. Chem. 2017, 89 (14), 7631–7640. (Nature Index期刊)

(22) Ji, H.; Xu, Y.; Lu, H.; Zhang, Z. Deep MS/MS-Aided Structural-Similarity Scoring for Unknown Metabolite Identification. Anal. Chem. 2019, 91 (9), 5629–5637. (Nature Index期刊)

(23) Ji, H.; Lu, H.; Zhang, Z. Pure Ion Chromatogram Extraction: Via Optimal k -Means Clustering. RSC Adv. 2016, 6 (62), 56977–56985.

代表性专利

(1)  纪宏超; 化合物的化学结构确定方法、装置及终端设备, 2023-12-7, 中国, ZL 2023 1 1690470.0 (已授权)

(2)  纪宏超; 陈顺兴; 一种提高化合物与蛋白质相互作用实验通量的方法, 2022-6-7, 中国, 202210638301.1 (申请)

(3)  Ji Hongchao; Soon Heng Tan; Method for Improving Throughput of Compound-Protein Interaction, 2023-6-5, 美国, PCT/CN2023/098376 (申请)

纪宏超课题组更新于2026年7月23日