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Lijun Quan
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2020 – today
- 2024
- [j19]Xuejiao Wang, Tingfang Wu
, Yelu Jiang
RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding. Bioinform. 40(1) (2024) - [j18]Junkai Wang
MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction. IEEE J. Biomed. Health Informatics 28(8): 4995-5006 (2024) - 2023
- [j17]Zhi Jin, Tingfang Wu, Taoning Chen, Deng Pan, Xuejiao Wang, Jingxin Xie, Lijun Quan, Qiang Lyu:
CAPLA: improved prediction of protein-ligand binding affinity by a deep learning approach based on a cross-attention mechanism. Bioinform. 39(2) (2023) - [j16]Kailong Li, Lijun Quan
Simultaneous Prediction of Interaction Sites on the Protein and Peptide Sides of Complexes through Multilayer Graph Convolutional Networks. J. Chem. Inf. Model. 63(7): 2251-2262 (2023) - [j15]Jingxin Xie, Lijun Quan
DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features. J. Chem. Inf. Model. 63(22): 7258-7271 (2023) - [j14]Kailong Li, Lijun Quan
ctP2ISP: Protein-Protein Interaction Sites Prediction Using Convolution and Transformer With Data Augmentation. IEEE ACM Trans. Comput. Biol. Bioinform. 20(1): 297-306 (2023) - [j13]Lijun Quan
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. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 1594-1599 (2023) - [j12]Yelu Jiang, Lijun Quan
DGCddG: Deep Graph Convolution for Predicting Protein-Protein Binding Affinity Changes Upon Mutations. IEEE ACM Trans. Comput. Biol. Bioinform. 20(3): 2089-2100 (2023) - [j11]Taoning Chen
TransRNAm: Identifying Twelve Types of RNA Modifications by an Interpretable Multi-Label Deep Learning Model Based on Transformer. IEEE ACM Trans. Comput. Biol. Bioinform. 20(6): 3623-3634 (2023) - 2022
- [j10]Liangpeng Nie
TransPPMP: predicting pathogenicity of frameshift and non-sense mutations by a Transformer based on protein features. Bioinform. 38(10): 2705-2711 (2022) - [j9]Yan Li, Lijun Quan, Yiting Zhou, Yelu Jiang
Identifying modifications on DNA-bound histones with joint deep learning of multiple binding sites in DNA sequence. Bioinform. 38(17): 4070-4077 (2022) - [j8]Deng Pan, Lijun Quan
Multisource Attention-Mechanism-Based Encoder-Decoder Model for Predicting Drug-Drug Interaction Events. J. Chem. Inf. Model. 62(23): 6258-6270 (2022) - [j7]Lijun Quan
Learning Useful Representations of DNA Sequences From ChIP-Seq Datasets for Exploring Transcription Factor Binding Specificities. IEEE ACM Trans. Comput. Biol. Bioinform. 19(2): 998-1008 (2022) - [i1]Yikang Zhang, Xiaomin Chu, Yelu Jiang, Hongjie Wu, Lijun Quan:
SemanticCAP: Chromatin Accessibility Prediction Enhanced by Features Learning from a Language Model. CoRR abs/2204.02130 (2022) - 2021
- [j6]Lijun Quan
Quantifying Intensities of Transcription Factor-DNA Binding by Learning From an Ensemble of Protein Binding Microarrays. IEEE J. Biomed. Health Informatics 25(7): 2811-2819 (2021) - 2020
- [j5]Lijun Quan
Developing parallel ant colonies filtered by deep learned constrains for predicting RNA secondary structure with pseudo-knots. Neurocomputing 384: 104-114 (2020)
2010 – 2019
- 2019
- [j4]Buzhong Zhang, Jinyan Li, Lijun Quan, Yu Chen, Qiang Lü:
Sequence-based prediction of protein-protein interaction sites by simplified long short-term memory network. Neurocomputing 357: 86-100 (2019) - 2016
- [j3]Lijun Quan, Qiang Lv, Yang Zhang
STRUM: structure-based prediction of protein stability changes upon single-point mutation. Bioinform. 32(19): 2936-2946 (2016) - 2014
- [j2]Lijun Quan, Qiang Lü, Haiou Li, Xiaoyan Xia, Hongjie Wu:
Improved packing of protein side chains with parallel ant colonies. BMC Bioinform. 15(S-12): S5 (2014) - 2013
- [j1]Hongjie Wu, Qiang Lü, Lijun Quan, Peide Qian, Xiaoyan Xia:
patGPCR: A Multitemplate Approach for Improving 3D Structure Prediction of Transmembrane Helices of G-Protein-Coupled Receptors. Comput. Math. Methods Medicine 2013: 486125:1-486125:12 (2013) - [c2]Lijun Quan, Haiou Li, Xiaoyan Xia, Qiang Li:
Packing protein side-chains by parallel ant colonies. BIBM 2013: 10-16 - [c1]Haiou Li, Qiang Lu, Rong Chen, Lijun Quan, Xiaoyan Xia:
A protein-peptide docking program with modeling receptor flexible areas. BIBM 2013: 48-50
Coauthor Index
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