Predicting Essential Proteins Based on Gene Expression Data, Subcellular Localization and PPI Data. - Xiujuan Lei; Siguo Wang; Linqiang Pan (BIC-TA, 2017)

Identifying Essential Proteins in Dynamic PPI Network with Improved FOA. - Xiujuan Lei; Siguo Wang; Linqiang Pan (Int. J. Comput. Commun. Control, 2018)

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)

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)

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)

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)

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)

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)

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

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)