A protein-peptide docking program with modeling receptor flexible areas. - Haiou Li; Qiang Lü; Rong Chen; Lijun Quan; Xiaoyan Xia (BIBM, 2013)

Packing protein side-chains by parallel ant colonies. - Lijun Quan; Haiou Li; Xiaoyan Xia; Qiang Li (BIBM, 2013)

patGPCR: A Multitemplate Approach for Improving 3D Structure Prediction of Transmembrane Helices of G-Protein-Coupled Receptors. - Hongjie Wu; Qiang Lü; Lijun Quan; Peide Qian; Xiaoyan Xia (Comput. Math. Methods Medicine, 2013)

Improved packing of protein side chains with parallel ant colonies. - Lijun Quan; Qiang Lü; Haiou Li; Xiaoyan Xia; Hongjie Wu (BMC Bioinform., 2014)

STRUM: structure-based prediction of protein stability changes upon single-point mutation. - Lijun Quan; Qiang Lv; Yang Zhang 040 (Bioinform., 2016)

Sequence-based prediction of protein-protein interaction sites by simplified long short-term memory network. - Buzhong Zhang; Jinyan Li 001; Lijun Quan; Yu Chen 064; Qiang Lü (Neurocomputing, 2019)

Developing parallel ant colonies filtered by deep learned constrains for predicting RNA secondary structure with pseudo-knots. - Lijun Quan; Leixin Cai; Yu Chen 064; Jie Mei; Xiaoyu Sun 006; Qiang Lyu (Neurocomputing, 2020)

Quantifying Intensities of Transcription Factor-DNA Binding by Learning From an Ensemble of Protein Binding Microarrays. - Lijun Quan; Jie Mei; Ruji He; Xiaoyu Sun 006; Liangpeng Nie; Kailong Li; Qiang Lyu (IEEE J. Biomed. Health Informatics, 2021)

Identifying modifications on DNA-bound histones with joint deep learning of multiple binding sites in DNA sequence. - Yan Li; Lijun Quan; Yiting Zhou; Yelu Jiang; Kailong Li; Tingfang Wu; Qiang Lyu (Bioinform., 2022)

TransPPMP: predicting pathogenicity of frameshift and non-sense mutations by a Transformer based on protein features. - Liangpeng Nie; Lijun Quan; Tingfang Wu; Ruji He; Qiang Lyu (Bioinform., 2022)

SemanticCAP: Chromatin Accessibility Prediction Enhanced by Features Learning from a Language Model. - Yikang Zhang; Xiaomin Chu; Yelu Jiang; Hongjie Wu; Lijun Quan (CoRR, 2022)

Multisource Attention-Mechanism-Based Encoder-Decoder Model for Predicting Drug-Drug Interaction Events. - Deng Pan; Lijun Quan; Zhi Jin; Taoning Chen; Xuejiao Wang; Jingxin Xie; Tingfang Wu; Qiang Lyu (J. Chem. Inf. Model., 2022)

Learning Useful Representations of DNA Sequences From ChIP-Seq Datasets for Exploring Transcription Factor Binding Specificities. - Lijun Quan; Xiaoyu Sun 006; Jian Wu; Jie Mei; Liqun Huang; Ruji He; Liangpeng Nie; Yu Chen 064; Qiang Lyu (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

TransRNAm: Identifying Twelve Types of RNA Modifications by an Interpretable Multi-Label Deep Learning Model Based on Transformer. - Taoning Chen; Tingfang Wu; Deng Pan; Jinxing Xie; Jin Zhi; Xuejiao Wang; Lijun Quan; Qiang Lyu (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

DGCddG: Deep Graph Convolution for Predicting Protein-Protein Binding Affinity Changes Upon Mutations. - Yelu Jiang; Lijun Quan; Kailong Li; Yan Li; Yiting Zhou; Tingfang Wu; Qiang Lyu (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

ctP2ISP: Protein-Protein Interaction Sites Prediction Using Convolution and Transformer With Data Augmentation. - Kailong Li; Lijun Quan; Yelu Jiang; Yan Li; Yiting Zhou; Tingfang Wu; Qiang Lyu (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

How Deepbics Quantifies Intensities of Transcription Factor-DNA Binding and Facilitates Prediction of Single Nucleotide Variant Pathogenicity With a Deep Learning Model Trained On ChIP-Seq Data Sets. - Lijun Quan; Xiaomin Chu; Xiaoyu Sun 006; Tingfang Wu; Qiang Lyu (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

CAPLA: improved prediction of protein-ligand binding affinity by a deep learning approach based on a cross-attention mechanism. - Zhi Jin; Tingfang Wu; Taoning Chen; Deng Pan; Xuejiao Wang; Jingxin Xie; Lijun Quan; Qiang Lyu (Bioinform., 2023)

Simultaneous Prediction of Interaction Sites on the Protein and Peptide Sides of Complexes through Multilayer Graph Convolutional Networks. - Kailong Li; Lijun Quan; Yelu Jiang; Hongjie Wu; Jian Wu; Yan Li; Yiting Zhou; Tingfang Wu; Qiang Lyu (J. Chem. Inf. Model., 2023)

DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features. - Jingxin Xie; Lijun Quan; Xuejiao Wang; Hongjie Wu; Zhi Jin; Deng Pan; Taoning Chen; Tingfang Wu; Qiang Lyu (J. Chem. Inf. Model., 2023)

Research on Scenario-Based Dynamic Inspection Methodology Using Expression Engine. - Jian Wu; Jun Yao; Guohui Li; Jianhong Gu; Lijun Quan (ITU K, 2024)

DCMA: faster protein backbone dihedral angle prediction using a dilated convolutional attention-based neural network. - Buzhong Zhang; Meili Zheng; Yuzhou Zhang; Lijun Quan (Frontiers Bioinform., 2024)

RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding. - Xuejiao Wang; Tingfang Wu; Yelu Jiang; Taoning Chen; Deng Pan; Zhi Jin; Jingxin Xie; Lijun Quan; Qiang Lyu (Bioinform., 2024)

MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction. - Junkai Wang; Lijun Quan; Zhi Jin; Hongjie Wu; Xuhao Ma; Xuejiao Wang; Jingxin Xie; Deng Pan; Taoning Chen; Tingfang Wu; Qiang Lyu (IEEE J. Biomed. Health Informatics, 2024)

DS-MVP: identifying disease-specific pathogenicity of missense variants by pre-training representation. - Qiufeng Chen; Lijun Quan; Lexin Cao; Bei Zhang; Zhijun Zhang; Liangchen Peng; Junkai Wang; Yelu Jiang; Liangpeng Nie; Geng Li; Tingfang Wu; Qiang Lyu (Briefings Bioinform., 2025)

AffiGrapher: Contrastive Heterogeneous Graph Learning with Aromatic Virtual Nodes for RNA-Small Molecule Binding Affinity Prediction. - Junkai Wang; Jian Wu; Zhijun Zhang; Yelu Jiang; Liangchen Peng; Bei Zhang; Qiufeng Chen; Lexin Cao; Lijun Quan; Qiang Lyu (J. Chem. Inf. Model., 2025)

MMSol: Predicting Protein Solubility with an Antinoise Multimodal Deep Model. - Jia Xu; Tingfang Wu; Yelu Jiang; Liangpeng Nie; Geng Li; Yi Zhang; Zhenglong Zhou; Yiwei Chen; Lijun Quan; Qiang Lyu (J. Chem. Inf. Model., 2025)

MVCL-DTI: Predicting Drug-Target Interactions Using a Multiview Contrastive Learning Model on a Heterogeneous Graph. - Bei Zhang; Lijun Quan; Zhijun Zhang; Lexin Cao; Qiufeng Chen; Liangchen Peng; Junkai Wang; Yelu Jiang; Liangpeng Nie; Geng Li; Tingfang Wu; Qiang Lyu (J. Chem. Inf. Model., 2025)

AACDR: Integrating Graph Isomorphism Networks and Asymmetric Adversarial Domain Adaptation for Cancer Drug Response Prediction. - Yi Zhang; Tingfang Wu; Liangpeng Nie; Yelu Jiang; Geng Li; Jia Xu; Zhenglong Zhou; Yiwei Chen; Lijun Quan; Qiang Lyu (J. Chem. Inf. Model., 2025)