Comparative study of two-layer particle swarm optimization and particle swarm optimization in classification for tumor gene expression data with different dimensionalities. - Yajie Liu; Xinling Shi; Baolei Li; Lian Gao; Changxing Gou; Qinhu Zhang; Yunchao Huang (BMEI, 2013)

Path planning based on firefly algorithm and Bezier curve. - Baolei Li; Lan-juan Liu; Qinhu Zhang; Danjv Lv; Yufeng Zhang 002; Junhua Zhang 001; Xinling Shi (ICIA, 2014)

A novel heuristic algorithm in field GIS-based emergency path finding. - Danjv Lv; Xinling Shi; Baolei Li; Qinhu Zhang; Lian Gao; Yufeng Zhang 002; Junhua Zhang 001 (ICIA, 2014)

On the convergence of multivariant optimization algorithm. - Baolei Li; Jianhua Chen 001; Xinling Shi; Yufeng Zhang 002; Danjv Lv; Lan-juan Liu; Qinhu Zhang (Appl. Soft Comput., 2016)

Data clustering using multivariant optimization algorithm. - Qinhu Zhang; Baolei Li; Yajie Liu; Lian Gao; Lan-juan Liu; Xinling Shi (Int. J. Mach. Learn. Cybern., 2016)

Motif Discovery via Convolutional Networks with K-mer Embedding. - Dailun Wang; Qinhu Zhang; Chang-An Yuan 001; Xiao Qin 005; Zhi-Kai Huang; Li Shang (ICIC (2), 2019)

High-Order Convolutional Neural Network Architecture for Predicting DNA-Protein Binding Sites. - Qinhu Zhang; Lin Zhu 008; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Three-Layer Dynamic Transfer Learning Language Model for E. Coli Promoter Classification. - Ying He; Zhen Shen; Qinhu Zhang; Siguo Wang; Changan Yuan 001; Xiao Qin 005; Hongjie Wu; Xingming Zhao (ICIC (2), 2020)

A New Method Combining DNA Shape Features to Improve the Prediction Accuracy of Transcription Factor Binding Sites. - Siguo Wang; Zhen Shen; Ying He; Qinhu Zhang; Changan Yuan 001; Xiao Qin 005; Hongjie Wu; Xingming Zhao (ICIC (2), 2020)

Predicting in-Vitro Transcription Factor Binding Sites with Deep Embedding Convolution Network. - Yindong Zhang; Qinhu Zhang; Changan Yuan 001; Xiao Qin 005; Hongjie Wu; Xingming Zhao (ICIC (2), 2020)

Weakly-Supervised Convolutional Neural Network Architecture for Predicting Protein-DNA Binding. - Qinhu Zhang; Lin Zhu 008; Wenzheng Bao; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

A survey on deep learning in DNA/RNA motif mining. - Ying He; Zhen Shen; Qinhu Zhang; Siguo Wang; De-Shuang Huang (Briefings Bioinform., 2021)

Locating transcription factor binding sites by fully convolutional neural network. - Qinhu Zhang; Siguo Wang; Zhanheng Chen; Ying He; Qi Liu 019; De-Shuang Huang (Briefings Bioinform., 2021)

Special issue: Advanced Intelligent Computing Theory and Applications in Big Data Era. - Qinhu Zhang; Vitoantonio Bevilacqua; De-Shuang Huang (Neurocomputing, 2021)

Predicting in-vitro Transcription Factor Binding Sites Using DNA Sequence + Shape. - Qinhu Zhang; Zhen Shen; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Predicting TF-DNA Binding Motifs from ChIP-seq Datasets Using the Bag-Based Classifier Combined With a Multi-Fold Learning Scheme. - Qinhu Zhang; Dailun Wang; Kyungsook Han; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Multi-Scale Capsule Network for Predicting DNA-Protein Binding Sites. - Qinhu Zhang; Wenbo Yu; Kyungsook Han; Asoke K. Nandi; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Base-resolution prediction of transcription factor binding signals by a deep learning framework. - Qinhu Zhang; Ying He; Siguo Wang; Zhanheng Chen; Zhen-Hao Guo; Zhen Cui; Qi Liu 019; De-Shuang Huang (PLoS Comput. Biol., 2022)

RMSCNN: A Random Multi-Scale Convolutional Neural Network for Marine Microbial Bacteriocins Identification. - Zhen Cui; Zhan-Heng Chen; Qinhu Zhang; Valeriya V. Gribova; Vladimir Fedorovich Filaretov; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

A Deep Learning Model for RNA-Protein Binding Preference Prediction Based on Hierarchical LSTM and Attention Network. - Zhen Shen; Qinhu Zhang; Kyungsook Han; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Predicting In-Vitro DNA-Protein Binding With a Spatially Aligned Fusion of Sequence and Shape. - Qinhu Zhang; Yindong Zhang; Siguo Wang; Zhan-Heng Chen; Valeriya V. Gribova; Vladimir Fedorovich Filaretov; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

FCNGRU: Locating Transcription Factor Binding Sites by Combing Fully Convolutional Neural Network With Gated Recurrent Unit. - Siguo Wang; Ying He; Zhanheng Chen; Qinhu Zhang (IEEE J. Biomed. Health Informatics, 2022)

DLoopCaller: A deep learning approach for predicting genome-wide chromatin loops by integrating accessible chromatin landscapes. - Siguo Wang; Qinhu Zhang; Ying He; Zhen Cui; Zhen-Hao Guo; Kyungsook Han; De-Shuang Huang (PLoS Comput. Biol., 2022)

Lightweight Traffic Sign Recognition Model Based on Dynamic Feature Extraction. - Yiyuan Ge; Ke Niu 002; Zhihao Chen; Qinhu Zhang (ICAI (1), 2023)

In silico prediction methods of self-interacting proteins: an empirical and academic survey. - Zhanheng Chen; Zhuhong You; Qinhu Zhang; Zhen-Hao Guo; Siguo Wang; Yanbin Wang (Frontiers Comput. Sci., 2023)

iCircDA-NEAE: Accelerated attribute network embedding and dynamic convolutional autoencoder for circRNA-disease associations prediction. - Lin Yuan 001; Jiawang Zhao; Zhen Shen; Qinhu Zhang; Yushui Geng; Chun-Hou Zheng 001; De-Shuang Huang (PLoS Comput. Biol., 2023)

Predicting the Sequence Specificities of DNA-Binding Proteins by DNA Fine-Tuned Language Model With Decaying Learning Rates. - Ying He; Qinhu Zhang; Siguo Wang; Zhanheng Chen; Zhen Cui; Zhen-Hao Guo; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Using Fully Convolutional Network to Locate Transcription Factor Binding Sites Based on DNA Sequence and Conservation Information. - Qinhu Zhang; Youhong Xu; Siguo Wang; Yong Wu; Yuan-Nong Ye; Chang-An Yuan 001; Valeriya V. Gribova; Vladimir Fedorovich Filaretov; De-Shuang Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Computational prediction and characterization of cell-type-specific and shared binding sites. - Qinhu Zhang; Pengrui Teng; Siguo Wang; Ying He; Zhen Cui; Zhenghao Guo; Yixin Liu; Changan Yuan 001; Qi Liu 019; De-Shuang Huang (Bioinform., 2023)

DeepTPpred: A Deep Learning Approach With Matrix Factorization for Predicting Therapeutic Peptides by Integrating Length Information. - Zhen Cui; Siguo Wang; Ying He; Zhan-Heng Chen; Qinhu Zhang (IEEE J. Biomed. Health Informatics, 2023)

scInterpreter: a knowledge-regularized generative model for interpretably integrating scRNA-seq data. - Zhen-Hao Guo; Yan Wu; Siguo Wang; Qinhu Zhang; Jin-Ming Shi; Yan-Bin Wang; Zhan-Heng Chen (BMC Bioinform., 2023)

PreZ-DGGAN: A Drug Graph GAN Based on Pre-Learning of Implicit Variables. - Yixin Liu; Yueqin Fan; Zhipeng Li; Qinhu Zhang (ICAI (1), 2024)

Enhancing Medical Image Report Generation Through Regional and Global Feature Interaction. - Pengrui Teng; Hongyu Yang; Qinhu Zhang (ICAI (1), 2024)

Predicting Transcription Factor Binding Signals Based on a Novel Encoder-Decoder Framework. - Siguo Wang; Zhipeng Li 001; Qinhu Zhang (ICAI (1), 2024)

Single Cell Clustering Based on Multi-view Generation. - Yueyue Wang; Zheyu Wu; Qinhu Zhang (ICAI (1), 2024)

scMGCAE: A Masked Graph Cluster Autoencoder for Single-Cell RNA-Seq Clustering. - Zheyu Wu; Yueyue Wang; Qinhu Zhang (ICAI (1), 2024)

Harnessing Elastic Adaptive Learning Network for Low-Light Image Enhancement. - Meng Xing; Xiaomei Li; Qinhu Zhang (ICAI (2), 2024)

Exploration of Neural Radiance Fields, A Review. - Meng Xing; Shaoyang Qu; Qinhu Zhang (ICAI (2), 2024)

Restoring Missing Slices of Serial Section Electron Microscopy Using Diffusion Models. - Hongyu Yang; Ruobing Zhang; Qinhu Zhang (ICAI (2), 2024)

Domain Adaptation for Semantic Segmentation of Cataract Surgical Images Based on Masked Image Consistency. - Yuzhu Zhang; Yijie Pan; Mingyang Ou; Guanghui Gong; Qinhu Zhang; Haojin Li; Heng Li (ICAI (1), 2024)

A Data Augmentation Method for Disease Diagnosis Based on Single Cell Omics Data. - Han Zhuang; Qinhu Zhang (ICAI (1), 2024)

Dynamic Link Prediction for New Nodes in Temporal Graph Networks. - Xiaobo Zhu; Yan Wu; Qinhu Zhang; Zhanheng Chen; Ying He (IJCNN, 2024)

scRGCL: a cell type annotation method for single-cell RNA-seq data using residual graph convolutional neural network with contrastive learning. - Lin Yuan 001; Shengguo Sun; Yufeng Jiang; Qinhu Zhang; Lan Ye; Chun-Hou Zheng 001; De-Shuang Huang (Briefings Bioinform., 2024)

scMGATGRN: a multiview graph attention network-based method for inferring gene regulatory networks from single-cell transcriptomic data. - Lin Yuan 001; Ling Zhao; Yufeng Jiang; Zhen Shen; Qinhu Zhang; Ming Zhang; Chun-Hou Zheng 001; De-Shuang Huang (Briefings Bioinform., 2024)

Identification of ferroptosis-related lncRNAs for predicting prognosis and immunotherapy response in non-small cell lung cancer. - Lin Yuan 001; Shengguo Sun; Qinhu Zhang; Hai-Tao Li; Zhen Shen; Chunyu Hu 001; Xiaogang Zhao; Lan Ye; Chun-Hou Zheng 001; De-Shuang Huang (Future Gener. Comput. Syst., 2024)

iCRBP-LKHA: Large convolutional kernel and hybrid channel-spatial attention for identifying circRNA-RBP interaction sites. - Lin Yuan 001; Ling Zhao; Jinling Lai; Yufeng Jiang; Qinhu Zhang; Zhen Shen; Chun-Hou Zheng 001; De-Shuang Huang (PLoS Comput. Biol., 2024)

scCorrector: a robust method for integrating multi-study single-cell data. - Zhen-Hao Guo; Yan-Bin Wang; Siguo Wang; Qinhu Zhang; De-Shuang Huang (Briefings Bioinform., 2024)

Hierarchical Multiview Top-k Pooling With Deep-Q-Networks. - Zhi-Peng Li 002; Hai-Long Su; Yong Wu; Qinhu Zhang; Chang-an Yuan 001; Valeriya V. Gribova; Vladimir Fedorovich Filaretov; De-Shuang Huang (IEEE Trans. Artif. Intell., 2024)

RGCN-BA: relational graph convolutional network with batch awareness for single-cell RNA sequencing clustering. - Yueyue Wang; Pengrui Teng; Zheyu Wu; Yuna Zhang; Zhisen Shen; Qinhu Zhang; De-Shuang Huang (Briefings Bioinform., 2025)

A brief survey of deep learning-based models for CircRNA-protein binding sites prediction. - Zhen Shen; Lin Yuan 001; Wenzheng Bao; Siguo Wang; Qinhu Zhang; De-Shuang Huang (Neurocomputing, 2025)

Graph pooling for graph-level representation learning: a survey. - Zhi-Peng Li 002; Siguo Wang; Qinhu Zhang; Yi-Jie Pan; Naian Xiao; Jiayang Guo; Chang-An Yuan 001; Wen-Jian Liu; De-Shuang Huang (Artif. Intell. Rev., 2025)

NPENN: A Noise Perturbation Ensemble Neural Network for Microbiome Disease Phenotype Prediction. - Zhen Cui; Yan Wu 011; Qinhu Zhang; Siguo Wang; Zhen-Hao Guo (IEEE J. Biomed. Health Informatics, 2025)