代表论文：

1. Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks. Nature Communications. 2023, 14: 6155 (codes)
2. Inferring gene regulatory network from single-cell transcriptomes with graph autoencoder model. PLoS Genetics. 2023, 19(9): e1010942 (codes)
3. A computational model of circRNA-associated diseases based on a graph neural network: prediction, and case studies for follow-up experimental validation. BMC Biology. 2024, 22:24. (codes)
4. Prediction of protein solubility based on sequence physicochemical patterns and distributed representation information with DeepSoluE. BMC Biology. 2023, 21:12. (web server)
5. m5U-SVM: Identification of RNA 5-methyluridine modification sites based on multi-view features of physicochemical features and distributed representation. BMC Biology. 2023, 21: 93(web server)
6. MRMD3.0: A Python tool and webserver for dimensionality reduction and data visualization via an ensemble strategy. Journal of Molecular Biology. 2023, 435: 168116 (web site)
7. HAlign 3: fast multiple alignment of ultra-large numbers of similar DNA/RNA sequences. Molecular Biology and Evolution. 2022,39(8):msac166. (codes)
8. TPMA: a two pointers meta-alignment tool to ensemble different multiple nucleic acid sequence alignments. PLoS Computational Biology. 2024, 20(4): e1011988 (codes)
9. AutoEdge-CCP: A Novel Approach for Predicting Cancer-Associated CircRNAs and Drugs based on Automated Edge Embedding. PLoS Computational Biology. 2024, 20(1): e1011851 (codes)
10. A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data. PLoS Computational Biology. 2022, 18(9): e1010402 (codes)
11. A comprehensive overview and evaluation of circular RNA detection tools. PLoS Computational Biology. 2017,13(6): e1005420 (SCI, IF2017=3.955, PMID: 28594838) (data and codes)(BibTeX, EndNote)
12. Gene2vec: Gene Subsequence Embedding for Prediction of Mammalian N6‐Methyladenosine Sites from mRNA. RNA. 2019, 25(2): 205-218 (SCI, IF2017=4.490, PMID: 30425123) (web server)(BibTeX, EndNote)


13. RAVAR: a curated repository for rare variant-trait associations. Nucleic Acids Research. 2024, 52(D1): D990-D997. (web server)
14. webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study. Nucleic Acids Research. 2022, 50(D1): D1123-D1130. (web site)
15. DeepBIO: An automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation, and visualization analysis. Nucleic Acids Research. 2023, 51(7): 3017-3029. (web server)


16. PaGeFinder: Quantitative Identification of Spatiotemporal Pattern Genes. Bioinformatics. 2012, 28(11):1544-1545. (SCI, IF2017=5.481, PMID:22492640)(Web Server)(BibTeX, EndNote)
17. HAlign: Fast Multiple Similar DNA/RNA Sequence Alignment Based on the Centre Star Strategy. Bioinformatics. 2015,31(15): 2475-2481. (SCI, IF2017=5.481, PMID: 25812743) (Software)(该软件被OMICTOOLS推荐)(BibTeX, EndNote)
18. Tumor Origin Detection with Tissue-Specific miRNA and DNA methylation Markers. Bioinformatics. 2018, 34(3): 398-406. (SCI, IF2017=5.481, PMID:29028927) (web server) (BibTeX, EndNote)
19. O-GlcNAcPRED-II: an integrated classification algorithm for identifying O-GlcNAcylation sites based on fuzzy undersampling and a K-means PCA oversampling technique. Bioinformatics. 2018, 34(12): 2029-2036. (SCI, IF2017=5.481, PMID:29420699)(web server)(该软件被OMICTOOLS推荐)(BibTeX, EndNote)
20. Prediction of potential disease-associated microRNAs using structural perturbation method. Bioinformatics. 2018, 34(14): 2425-2432.(SCI, IF2017=5.481, PMID:29490018)(codes)(BibTeX, EndNote)
21. 4mCPred: Machine Learning Methods for DNA N⁴-methylcytosine sites Prediction. Bioinformatics. 2019, 35(4): 593-601 (SCI, IF2017=5.481, PMID: 30052767)(web server)(该软件被OMICTOOLS推荐)
22. Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species. Bioinformatics. 2019, 35(8): 1326-1333. (SCI, IF2017=5.481, PMID: 30239627)(web server)
23. PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning. Bioinformatics. 2019, 35(21):4272-4280. (SCI, IF2017=5.481, PMID:30994882) (web server)
24. Iterative feature representations improve N4-methylcytosine site prediction. Bioinformatics. 2019, 35(23): 4930-4937. (SCI, IF2017=5.481, PMID:31099381)(web server)
25. StackCPPred: A Stacking and Pairwise Energy Content based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency. Bioinformatics. 2020, 36(10):3028-3034. (code)
26. PPTPP: A novel therapeutic peptide prediction method using physicochemical property encoding and adaptive feature representation learning. Bioinformatics. 2020, 36(13): 3982-3987 (codes and data)
27. Basic polar and hydrophobic properties are the main characteristics that affect the binding of transcription factors to methylation sites. Bioinformatics. 2020,36(15):4263-4268 (Supplementary data)
28. Identification of Sub-Golgi Protein Localization by Use of Deep Representation Learning Features. Bioinformatics. 2020, 36(24):5600-5609 (web server)
29. BP4RNAseq: a babysitter package for retrospective and newly generated RNA-seq data analyses using both alignment-based and alignment-free quantification methods. Bioinformatics. 2021, 37(9):1319-1321. (codes) High impact research from Bioinformatics
30. DeepAc4C: A convolutional neural network model with hybrid features composed of physico-chemical patterns and distributed representation information for identification of N4 acetylcytidine in mRNA. Bioinformatics. 2022, 38(1): 52-57. (web server)
31. NerLTR-DTA: Drug-target binding affinity prediction based on neighbor relationship and learning to rank. Bioinformatics. 2022, 38(7): 1964-1971. (codes and datasets)
32. GMNN2CD: Identification of circRNA–disease associations based on variational inference and graph Markov neural networks. Bioinformatics. 2022,38(8):2246-2253. (codes and data)
33. webSCST: an interactive web application for single-cell RNA-sequencing data and spatial transcriptomic data integration. Bioinformatics. 2022, 38(13):3488-3489. (web server)
34. Effector-GAN: prediction of fungal effector proteins based on pretrained deep representation learning methods and generative adversarial networks. Bioinformatics. 2022, 38(14):3541-3548. (web server)
35. i6mA-Caps: A CapsuleNet-based framework for identifying DNA N6-methyladenine sites. Bioinformatics. 2022, 38(16): 3885-3891. (web server)
36. CircSI-SSL: circRNA-binding site identification based on self-supervised learning. Bioinformatics. 2024, 40(1): btae004. (codes)
37. FMAlign2: A novel fast multiple nucleotide sequence alignment method for ultralong datasets. Bioinformatics. 2024, 40(1): btae014(codes)
38. Revisiting Drug-Protein Interaction Prediction: A Novel Global-Local Perspective. Bioinformatics. 2024, 40(5): btae271. (codes)
39. scTPC: a novel semi-supervised deep clustering model for scRNA-seq data. Bioinformatics. 2024, 40(5): btae293 (codes)
40. DeepAVP-TPPred: identification of antiviral peptides using transformed image-based localized descriptors and binary tree growth algorithm. Bioinformatics. 2024, 40(5): btae305 (codes)
41. Drug-target interaction predictions with multi-view similarity network fusion strategy and deep interactive attention mechanism. Bioinformatics. 2024, 40(6): btae346. (codes)
42. GraphADT: Empowering Interpretable Predictions of Acute Dermal Toxicity with Multi-View Graph Pooling and Structure Remapping. Bioinformatics. 2024, 40(7): btae438. (codes)


43. Sequence clustering in bioinformatics: an empirical study. Briefings in Bioinformatics. 2020,21(1): 1-10 (SCI, IF2017=6.302, PMID: 30239587)(data) Highly Cited Articles from Briefings in Bioinformatics
44. Prediction of bio-sequence modifications and the associations with diseases. Briefings in Functional Genomics. 2021, 20(1): 1-18 (data)Editor's Choice Highly Cited Articles from Briefings in Functional Genomics
45. CPPred-RF: a sequence-based predictor for identifying cell-penetrating peptides and their uptake efficiency. Journal of Proteome Research.2017, 16(5):2044-2053. (SCI, IF2018=3.780)(web server)(入选ACS出版社庆祝中科院建院70周年Highlight文章)
46. Prediction of human protein subcellular localization using deep learning. Journal of Parallel and Distributed Computing. 2018, 117: 212-217 (SCI, IF2017=1.815) most cited articles in this journal (BibTeX, EndNote)
47. Review and comparative analysis of machine learning-based phage virion protein identification methods. BBA - Proteins and Proteomics. 2020,1868(6):140406 Featured in the BBA Collection on "Viruses" and "Artificial Intelligence for biochemistry and molecular biology: AI is learning to help"
48. Multiple Sequence Alignment Based on a Suffix Tree and Center-Star Strategy: A Linear Method for Multiple Nucleotide Sequence Alignment on Spark Parallel Framework. Journal of Computational Biology. 2017, 24(12): 1230-1242 (SCI, IF2017=1.191, PMID: 29116822) (codes)(该软件被OMICTOOLS推荐)(BibTeX, EndNote)