RESEARCH DIRECTION: Studies on the application of AI-based Machine/deep learning algorithms in Cheminformatics, Bioinformatics and Medical informatics.
RESEARCH INTERESTS: Applying artificial intelligence-based technology to investigating the relationships between biological sequence, structure and functions; Modeling on interactions of biological moleculars (proteins, RNA and DNA) using machine-learning methods; Computer-aided drug investigation and design; Biological networks of disease-based biological multi-omics; Intelligent analysis and design on functional materials.
EDUCATION AND ACADEMIC CAREER:
2014/7 ~, Sichuan University, College of Chemistry, Associate Professor
2008/7 - 2014/6, Sichuan University, College of Chemistry, Lecturer
2003/9 - 2008/6, Sichuan University, College of Chemistry, Major on Analytical Chemistry，Doctor degree
SELECTED PUBLICATIONS:
1. Hao Lan, Jinyi Zhao, Linxi Yuan, Menglong Li, Xuemei Pu, Yanzhi Guo*. Deep clustering-based immunotherapy prediction of gastric cancer with mRNA vaccine development. International Journal of Molecular Sciences, 2025, 26, 2453.
2. Yanling Wu, Menglong Li, Jinru Shen, Xuemei Pu, Yanzhi Guo*. A consensual machine-learning-assisted QSAR model for effective bioactivity prediction of xanthine oxidase inhibitors using molecular fingerprints. Molecular Diversity, 2024, 28(4): 2033-2048.
3. Jian He, Menglong Li, Jiangguo Qiu, Xuemei Pu, Yanzhi Guo*. HOPEXGB: a consensual model for predicting miRNA/lncRNA-disease associations using a heterogeneous disease-miRNA-lncRNA information network. Journal of Chemical Information and Modeling, 2024, 64(7): 2863-2877.
4. Lingyan Wu, Kun Li, Menglong Li, Xuemei Pu, Yanzhi Guo*. Attention Mechanism-Based Graph Neural Network Model for Effective Activity Prediction of SARS-CoV-2 Main Protease Inhibitors: Application to Drug Repurposing as Potential COVID-19 Therapy. Journal of Chemical Information and Modeling, 2023, 63(22): 7011-7031.
5. Haiyan Li, Hao Lan, Menglong Li, Xuemei Pu, Yanzhi Guo*. A new molecular subclassification and in silico predictions for diagnosis and prognosis of papillary thyroid cancer by alternative splicing profile. Frontiers in Pharmacology, 2023, 14: 1119789.
6. Haiyan Li, Jian He, Menglong Li, Kun Li, Xuemei Pu, Yanzhi Guo*. Immune landscape-based machine-learning–assisted subclassification, prognosis, and immunotherapy prediction for glioblastoma. Frontiers in Immunology, 2022, 13: 1027631.
7. Jian He, Yanling Wu, Xuemei Pu, Menglong Li, Yanzhi Guo*. A transfer-learning-based deep convolutional neural network for predicting leukemia-related phosphorylation sites from protein primary sequences. International Journal of Molecular Sciences, 2022, 23, 1741.
8. Jian He, Xuemei Pu, Menglong Li,Chuan Li*, Yanzhi Guo*. Deep convolutional neural networks for predicting leukemia-related transcription factor binding sites from DNA sequence data. Chemometrics and Intelligent Laboratory Systems, 2020, 199, 103976
9. Jian He, Rongao Yuan, Lei Xu, Yanzhi Guo*, Menglong Li. Identification of disease-specific single amino acid polymorphisms using a simple random forest at protein-level. Current Bioinformatics, 2021, 16, 1278-1287.
10. Qihang Cai, Rongao Yuan, Jian He, Menglong Li, Yanzhi Guo*. Predicting HIV drug resistance using weighted machine learning method at target protein sequence-level. Molecular Diversity, 2021, 25: 1541-1551.
11. Lei Xu, Feng Liu, Haiyan Li, Menglong Li, Yongmei Xie, Zhihui Li*, Yanzhi Guo*. Comprehensive characterization of pathological stage‐related genes of papillary thyroid cancer along with survival prediction. Journal of Cellular and Molecular Medicine, 2021, 25(17): 8390-8404.
12. Haiyan Li, Feng Liu, Xiaoyang Wang, Menglong Li, Zhihui Li*, Yongmei Xie, Yanzhi Guo*. Identification of hub lncRNAs along with lncRNA-miRNA-mRNA network for effective diagnosis and prognosis of papillary thyroid cancer. Frontiers in Pharmacology, 2021, 12: 748867.
13. Lei Xu, Lei Zhang, Tian Wang, Yanling Wu, Xuemei Pu, Menglong Li, Yanzhi Guo*. ExoceRNA atlas: A database of cancer ceRNAs in human blood exosomes. Life Sciences, 2020, 257: 118092.
14. Lei Xu, Jian He, Qihang Cai, Menglong Li, Xuemei Pu, Yanzhi Guo*. An effective seven-CpG-based signature to predict survival in renal clear cell carcinoma by integrating DNA methylation and gene expression. Life sciences, 2020, 243: 117289.
15. Liu Qin, Yanhong Liu, Menglong Li*, Xuemei Pu and Yanzhi Guo*. The landscape of miRNA-related ceRNA networks for marking different renal cell carcinoma subtypes. Briefings in bioinformatics, 2020, 21(1): 73-84.
16. Youquan Liu, Yanzhi Guo*, Wengang Wu, Ying Xiong, Chuan Sun, Li Yuan, Menglong Li. A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection. Interdisciplinary Sciences: Computational Life Sciences, 2019, 11: 738-747.
17. Hao Qiu, Yanzhi Guo*, Lezheng Yu, Xuemei Pu, Menglong Li. Predicting protein lysine methylation sites by incorporating single-residue structural features into Chou's pseudo components. Chemometrics and Intelligent Laboratory Systems, 2018, 179: 31-38.
18. Wen Hu, Liu Qin, Menglong Li, Xuemei Pu, Yanzhi Guo*. Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction. Journal of Computer-Aided Molecular Design, 2018, 32: 1363-1373.
19. Wen Hu, Liu Qin, Menglong Li*, Xuemei Pu, Yanzhi Guo*. A structural dissection of protein-RNA interactions based on different RNA base areas of interfaces. RSC Advances, 2018, 8: 10582-10592.
20. Yu Wang, Yanzhi Guo*, Xuemei Pu, Menglong Li*. A sequence-based computational method for prediction of MoRFs. RSC Advances, 2017, 7: 18937-18945.
21. Yu Wang, Yun Lin, Yanzhi Guo*, Xuemei Pu, Menglong Li*. Functional dissection of human targets for KSHV-encoded miRNAs using network analysis. Scientific Reports, 2017, 7: 3159.
22. Yu Wang, Yanzhi Guo*, Xuemei Pu, Menglong Li. Effective prediction of bacterial type IV secreted effectors by combined features of both C-termini and N-termini. Journal of Computer-Aided Molecular Design, 2017, 11: 1029-1038.
23. Wenling Li, Yanzhi Guo*, Menglong Li, Xuemei Pu. Distinguishing the disease-associated SNPs based on composition frequency analysis. Interdisciplinary Sciences: Computational Life Sciences, 2017, 9: 459-467.
24. Zhongyu Liu, Yanzhi Guo*, Xuemei Pu, Menglong Li*. Dissecting the regulation rules of cancer-related miRNAs based on network analysis. Scientific Reports, 2016, 6: 34172.
25. Jiesi Luo, Wenling Li, Zhongyu Liu, Yanzhi Guo*, Xuemei Pu, Menglong Li*. A sequence-based two-level method for the prediction of type I secreted RTX proteins. Analyst, 2015, 140: 3048-3056.
26. Yayun Hu, Yanzhi Guo*, Yinan Shi, Menglong Li and Xuemei Pu*. A consensus subunit-specific model for annotation of substrate specificity for ABC transporters. RSC Advances, 2015, 5: 42009-42019.
27. Yinanshi, Yanzhi Guo*, Yayun Hu, Menglong Li*. Position-specific prediction of methylation sites from sequence conservation based on information theory. Scientific Reports, 2015, 5: 12403.
28. Xu Dai, Runyu Jing, Yanzhi Guo*, Yongcheng Dong, Yuelong Wang, Yuan Liu, Xuemei Pu, Menglong Li*. Predicting the Druggability of Protein-Protein Interactions Based on Sequence and Structure Features of Active Pockets. Current Pharmaceutical Design, 2015, 21: 3051-3061.
29. Jiesi Luo, Zhongyu Liu, Yanzhi Guo*, Menglong Li*. A structural dissection of large protein-protein crystal packing contacts. Scientific Reports, 2015, 5: 14214.
30. Yu Wang, Yanzhi Guo*, Qifan Kuang, Xuemei Pu, Yue Ji, Zhihang Zhang, Menglong Li*. A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach. Journal of Computer Aided Molecule Design, 2015, 29: 349-360.
31. Yuanyuan Fu, Yanzhi Guo*, Yuelong Wang, Jiesi Luo, Xuemei Pu, Menglong Li*, Zhihang Zhang. Exploring the relationship between hub proteins and drug targets based on GO and intrinsic disorder. Computational Biology and Chemistry, 2015, 56: 41-48.
32. Jiesi Luo, Yanzhi Guo*, Yuanyuan Fu, Yu Wang, Wenling Li, Menglong Li*. Effective discrimination between biologically relevant contacts and crystal packing contacts using new determinants. PROTEINS: structure, function, and bioinformatics, 2014, 82: 3090-3100.
33. Jiesi Luo, Yanzhi Guo*, Yun Zhong, Duo Ma, Wenling Li, Menglong Li*. A functional feature analysis on diverse protein-protein interactions: application for the prediction of binding affinity. Journal of Computer Aided Molecule Design, 2014, 28: 619-629.
34. Duo Ma, Yanzhi Guo*, Jiesi Luo, Xuemei Pu, Menglong Li*. Prediction of protein–protein binding affinity using diverse protein–protein interface features. Chemometrics and Intelligent Laboratory Systems, 2014, 138: 7-13.
35. Yun Zhong, Yanzhi Guo*, Jiesi Luo, Xuemei Pu, Menglong Li*. Effective identification of kinase-specific phosphorylation sites based on domain–domain interactions. Chemometrics and Intelligent Laboratory Systems, 2014, 136: 97-103.
36. Xiaojiao Yang, Yanzhi Guo*, Jiesi Luo, Xuemei Pu, Menglong Li*. Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles. PLoS ONE, 2013, 8(12): e84439.
37. Wen Liu, Yanzhi Guo*, Jiesi Luo, Yun Zhong, Xiaojiao Yang, Xuemei Pu, Menglong Li*. Prediction of kinase-specific phosphorylational interactions using random forest. Chemometrics and Intelligent Laboratory Systems, 2013, 126: 117-122.
38. Lezheng Yu, Jiesi Luo, Yanzhi Guo*, YizhouLi XuemeiPu, Menglong Li*. In Silico Identification of Gram-Negative Bacterial Secreted Proteins from Primary Sequence. Computational Biology and Medicine, 2013, 43: 1177-1181.
39. Jiesi Luo, Lezheng Yu, Yanzhi Guo*, Menglong Li*. Functional classification of secreted proteins by position specific scoring matrix and auto covariance. Computational Biology and Medicine, 2012, 110: 163-167.
40. Wenli Qin, Yizhou Li, Juan Li, Lezheng Yu, Di Wu, Runyu Jing, Xuemei Pu, Yanzh Guo*, Menglong Li*. Predicting deleterious non-synonymous single nucleotide polymorphisms in signal peptides based on hybrid sequence attributes. Computational Biology and Chemistry, 2012, 36: 31-35.
41. Xia Wang, Gang Mi, Cuicui Wang, Yongqing Zhang, Juan Li, Yanzhi Guo*, Xuemei Pu, Menglong Li*. Prediction of flavin mono-nucleotide binding sites using modified PSSM profile and ensemble support vector machine. Computational Biology and Medicine, 2012, 42(11): 1053-1059.
42. Juan Li, Yongqing Zhang, Wenli Qin, Yanzhi Guo*, Lezheng Yu, Xuemei Pu, Menglong Li, Jing Sun. Using the improved position specific scoring matrix and ensemble learning method to predict drug-binding residues from protein sequences. Natural Science, 2012, 4: 304-312.
43. Yanzhi Guo, Menglong Li*, Xuemei Pu, Gongbin Li, Juan Li. PRED_PPI: a server for predicting protein-protein interactions based on sequence data with probability assignment. BMC Research Notes, 2010, 3: 145.
44. Yanzhi Guo, Lezheng Yu, Zhining Wen, Menglong Li. Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences. Nucleic Acids Research, 2008, 36: 3025-3030.
45. Yanzhi Guo, Menglong Li, Minchun Lu, Zhining Wen, Kelong Wang, Gongbin Li, Jiang Wu. Classifying G protein-coupled receptors and nuclear receptors on the basis of protein power spectrum from fast Fourier transform. Amino Acids, 2006, 30: 397-402.
46. Yanzhi Guo, Menglong Li, Minchun Lu, Zhining Wen, Zhongtian Huang. Predicting G-protein coupled receptors-G-protein coupling specificity based on autocross-covariance transform. PROTEINS: structure, function, and bioinformatics, 2006, 65: 55-60.
47. Yanzhi Guo, Menglong Li, Kelong Wang, Zhining Wen, Minchun Lu, Lixia Liu, Lin Jiang. Fast Fourier Transform-based Support Vector Machine for Prediction of G-protein Coupled Receptor Subfamilies. Acta Biochimica et Biophysica Sinica, 2005, 37: 759-766.
