Yongxian Fan

Publications

[40] MLC-DTA: Drug-Target Affinity Prediction Based on Multi-Level Contrastive Learning and Equivariant Graph Neural Networks

Mengxin Zheng, Guicong Sun,and Yongxian Fan*
Neurocomputing(JCR Q1, IF: 6.5855), 2025, https://doi.org/10.1016/j.neucom.2025.130052

[39] MVGNCDA: Identifying Potential circRNA‑Disease Associations Based on Multi‑view Graph Convolutional Networks and Network Embeddings

Guicong Sun, Mengxin Zheng, Yongxian Fan*, and Xiaoyong Pan
Interdisciplinary Sciences: Computational Life Sciences(JCR Q1, IF:3.900), 2025, https://doi.org/10.1007/s12539-025-00690-x

[38] EGPDI: identifying Protein-DNA binding sites based on multi-view graph embedding fusion

Mengxin Zheng, Guicong Sun, XuePing Li, and Yongxian Fan*
BRIEFINGS IN BIOINFORMATICS(JCR Q1, IF:9.500), 2024, https://doi.org /10.1093/bib/bbae330

[37] iProL: identifying DNA promoters from sequence information based on Longformer pre-trained model

Binchao Peng, Guicong Sun, and Yongxian Fan*
BMC Bioinformatics(JCR Q2, IF: 2.900), 2024, https://doi.org /10.1186/s12859-024-05849-9

[36] An improved COVID-19 classification model on chest radiography by dual-ended multiple attention learning

Yongxian Fan*, and Hao Gong
IEEE Journal of Biomedical and Health Informatics(JCR Q1, SCI:7.7002), 2023, https://doi.org /10.1109/JBHI.2023.3324333

[35] An interpretable machine learning framework for diagnosis and prognosis of COVID-19

Yongxian Fan*, Meng Liu, and Guicong Sun
PLOS ONE(JCR Q2, SCI:3.7001), 2023, https://doi.org /10.1371/journal.pone.0291961

[34] IHCP: interpretable hepatitis C prediction system based on black-box machine learning models

Yongxian Fan*, Xiqian Lu, and Guicong Sun
BMC Bioinformatics(JCR Q2, SCI:2.9997), 2023, https://doi.org/10.1186/s12859-023-05456-0

[33] DeepASDPred: a CNN‑LSTM‑based deep learning method for Autism spectrum disorders risk RNA identification

Yongxian Fan, Hui Xiong, and Guicong Sun
BMC Bioinformatics(JCR Q2, SCI:2.9997), 2023, https://doi.org/10.1186/s12859-023-05378-x

[32] An improved tensor network for image classification in histopathology

Yongxian Fan*, and Hao Gong
The 5th Chinese Conference on Pattern Recognition and Computer Vision, 2022

[31] StackEPI: identification of cell line-specific enhancer-promoter interactions based on stacking ensemble learning

Yongxian Fan*, and Binchao Peng
BMC Bioinformatics(JCR Q2, SCI:2.9997), 2022, https://doi.org/10.1186/s12859-022-04821-9

[30] ELMo4m6A: a contextual language embedding-based predictor for detecting RNA N6-methyladenosine sites

Yongxian Fan*, Guicong Sun, and Xiaoyong Pan*
IEEE/ACM Transactions on Computational Biology and Bioinformatics(JCR Q1, SCI:4.5003), 2022, https://doi.org/10.1109/TCBB.2022.3173323

[29] Intrusion Detection Systems Based on Logarithmic Autoencoder and XGBoost

Wenfeng Xu, and Yongxian Fan*
Security and Communication Networks(JCR Q3, SCI:1.9682), 2022, https://doi.org/10.1155/2022/9068724

[28] Using Multi-Layer Perceptron to identify origins of replication in eukaryotes via informative features

Yongxian Fan*, and Wanru Wang
BMC Bioinformatics(JCR Q2, SCI:2.9997), 2021, https://doi.org/10.1186/s12859-021-04431-x

[27] Prediction of off-target Effects in CRISPR/CAS9 System by Ensemble Learning

Yongxian Fan*, and Haibo Xu
Current Bioinformatics(JCR Q1, SCI:4.0000), 2021, https://doi.org/10.2174/1574893616666210811100938

[26] GCRFLDA: Scoring lncRNA-disease associations using graph convolution matrix completion with conditional random field

Yongxian Fan*, Meijun Chen, and Xiaoyong Pan*
Briefings in Bioinformatics(JCR Q1, SCI:9.4998), 2021, https://doi.org/10.1093/bib/bbab361

[25] I2DS: Interpretable Intrusion Detection System using autoencoder and additive tree

Wenfeng Xu, Yongxian Fan*, and Changyong Li
Security and Communication Networks(JCR Q3, SCI:1.9682), 2021, https://doi.org/10.1155/2021/5564354

[24] PyConvU-Net: a lightweight and multiscale network for biomedical image segmentation

Changyong Li, Yongxian Fan*, and Xiaodong Cai
BMC Bioinformatics(JCR Q2, SCI:2.9997), 2021, https://doi.org/10.1186/s12859-020-03943-2

[23] lncLocPred: Predicting LncRNA Subcellular Localization Using Multiple Sequence Feature Information

Yongxian Fan*, Meijun Chen, and Qingqi Zhu
IEEE Access(JCR Q2, SCI:3.8001), 2020, https://doi.org/10.1109/ACCESS.2020.3007317

[22] Inferring Disease-associated Microbes Based on Multi-data Integration and Network Consistency Projection

Yongxian Fan*, Meijun Chen, Qingqi Zhu, and Wanru Wang
Frontiers in Bioengineering and Biotechnology(JCR Q1, SCI:5.6998), 2020, https://doi.org/10.3389/fbioe.2020.00831

[21] Fusing multiple biological networks to effectively predict miRNA-disease associations

Qingqi Zhu, Yongxian Fan*, and Xiaoyong Pan
Current Bioinformatics(JCR Q1, SCI:4.0000), 2020, https://doi.org/10.2174/1574893615999200715165335

[20] iterb-PPse: Identification of transcriptional terminators in bacterial by incorporating nucleotide properties into PseKNC

Yongxian Fan*, Wanru Wang, and Qingqi Zhu
PLOS ONE(JCR Q2, SCI:3.7001), 2020, https://doi.org/10.1371/journal.pone.0228479

[19] Heterogeneous graph inference based on similarity network fusion for predicting lncRNA-miRNA interaction

Yongxian Fan*, Juan Cui, and Qingqi Zhu
RSC Advances(JCR Q2, SCI:3.9003), 2020, https://doi.org/10.1039/C9RA11043G

[18] CNNPSP: Pseudouridine Sites Prediction Based on Deep Learning

Yong-xian Fan*, Yongzhen Li, Huihua Yang, and Xiaoyong Pan*
IDEAL 2019. Lecture Notes in Computer Science, 2019, https://doi.org/10.1007/978-3-030-33607-3_32

[17] Prediction of σ54 promoters in prokaryotes based on SVM–Adaboost

Yongxian Fan*, Qingqi Zhu, Chengwei Lv, and Xiaoyong Pan
2019 Chinese Automation Congress (CAC), 2019, https://doi.org/10.1109/CAC48633.2019.8997427

[16] Identifying RNA-binding proteins using multi-label deep learning

Xiaoyong Pan, Yong-Xian Fan, Jue Jia, and Hong-Bin Shen*
SCIENCE CHINA Information Sciences(JCR Q1, SCI:8.8005), 2019, https://doi.org/10.1007/s11432-018-9558-2

[15] LabCaS for ranking potential calpain substrate cleavage sites from amino acid sequence

Yong-Xian Fan, Xiaoyong Pan, Yang Zhang, and Hong-Bin Shen*
Messer J. (eds) Calpain. Methods in Molecular Biology, 2019, https://doi.org/10.1007/978-1-4939-8988-1_10

[14] DNA4mcEL：基于核苷酸信息特征计算分析与预测DNA N4-甲基胞嘧啶位点

龚浩, 樊永显*
中国生物化学与分子生物学报, 2019, 35(6): 633-647

[13] KELMPSP: 基于核极限学习机的假尿苷修饰位点识别

李永贞, 樊永显*, 杨辉华
中国生物化学与分子生物学报, 2018, 34(7): 785-793

[12] IPMiner: Hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction

Xiaoyong Pan^, Yong-Xian Fan^, Junchi Yan, and Hong-Bin Shen*
BMC Genomics(JCR Q1, SCI:4.3997), 2016, https://doi.org/10.1186/s12864-016-2931-8

[11] 基于标签和因子分析的协同推荐方法

蔡国永, 吕瑞, 樊永显
北京邮电大学学报, 2015, 33(9): 34-38

[10] Predicting pupylation sites in prokaryotic proteins using pseudo-amino acid composition and extreme learning machine

Yong-Xian Fan, and Hong-Bin Shen*
Neurocomputing(JCR Q2, SCI:5.9998), 2014, https://doi.org/10.1016/j.neucom.2012.11.058

[9] Predicting Protein-RNA Interaction Amino Acids using Random Forest Based on Submodularity Subset Selection

Xiaoyong Pan*, Lin Zhu, Yongxian Fan*, Junchi Yan
Computational Biology and Chemistry(JCR Q2, SCI:3.1000), 2014, https://doi.org/10.1016/j.compbiolchem.2014.11.002

[8] 基于一元线性回归的近红外光谱模型传递研究

杨辉华*, 张晓凤, 樊永显*, 谢谱模, 褚小立
分析化学, 2014, 42(9): 1229-1234

[7] LabCaS: Labeling calpain substrate cleavage sites from amino acid sequence using conditional random fields

Yong-Xian Fan, Yang Zhang, and Hong-Bin Shen*
PROTEINS: Structure, Function, and Bioinformatics(JCR Q3, SCI:2.8997), 2013, https://doi.org/10.1002/prot.24217

[6] Predicting protein N-terminal signal peptides using position-specific amino acid propensities and conditional random fields

Yong-Xian Fan, Jiangning Song, Chen Xu, and Hong-Bin Shen*
Current Bioinformatics(JCR Q1, SCI:4.0000), 2013, 8: 183-192

[5] Predicting protein-ATP binding sites from primary sequence through fusing bi-profile sampling of multi-view features

Ya-Nan Zhang^, Dong-Jun Yu^, Shu-Sen Li, Yong-Xian Fan, Yan Huang, and Hong-Bin Shen*
BMC Bioinformatics(JCR Q2, SCI:2.9997), 2012, https://doi.org/10.1186/1471-2105-13-118

[4] Signal-BNF: A Bayesian Network Fusing Approach to Predict Signal Peptides

Zhi Zheng, Youying Chen, Liping Chen, Gongde Guo, Yongxian Fan, and Xiangzeng Kong*
Journal of Biomedicine and Biotechnology, 2012, https://doi.org/10.1155/2012/492174

[3] PredCSF: An integrated feature-based approach for predicting conotoxin superfamily

Yong-Xian Fan, Jiangning Song, Xiangzeng Kong, and Hong-Bin Shen*
Protein and Peptide Letters(JCR Q4, SCI:1.6000), 2011, https://doi.org/10.2174/092986611794578341

[2] Conotoxin superfamily prediction using diffusion maps dimensionality reduction and subspace classifier

Jiang-Bo Yin^, Yong-Xian Fan^, and Hong-Bin Shen*
Current Protein and Peptide Science(JCR Q3, SCI:2.8002), 2011, https://doi.org/10.2174/138920311796957702

[1] 基于扩散映射和dHKNN算法的芋螺毒素超家族预测

尹江波, 雷剑波, 樊永显, 沈红斌*
Chinese Conference on Pattern Recognition 2010 (CCPR2010), Chongqing, China, Oct 21-23, 2010

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