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2020 – today
- 2024
[j24]Marc-Antoine Gerault
, Samuel Granjeaud, Luc Camoin, Pär Nordlund, Lingyun Dai:
IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of IMPRINTS-CETSA data. Briefings Bioinform. 25(3) (2024)- [j23]Tian-Jing Qiao, Feng Li, Shasha Yuan, Ling-Yun Dai, Juan Wang:
A Fusion Learning Model Based on Deep Learning for Single-Cell RNA Sequencing Data Clustering. J. Comput. Biol. 31(6): 576-588 (2024) - [j22]Yijie Bian, Jie Yang, Lingyun Dai, Xi Lin, Xinyao Cheng, Hang Que, Le Liang, Shi Jin:
Multi-modal fusion for sensing-aided beam tracking in mmWave communications. Phys. Commun. 67: 102514 (2024) - [j21]Xiaomeng Xue, Feng Li, Junliang Shang, Lingyun Dai, Daohui Ge, Qianqian Ren:
A feature extraction framework for discovering pan-cancer driver genes based on multi-omics data. Quant. Biol. 12(2): 173-181 (2024) - [c18]Qingwei Jia, Jin-Xing Liu, Junling Shang, Lingyun Dai, Yuxia Wang, Wenrong Hu, Shasha Yuan:
Seizure Types Classification Based on Multi-branch Hybrid Deep Learning Network. ICIC (4) 2024: 462-474 - [i1]Jin-Xing Liu, Wen-Yu Xi, Ling-Yun Dai, Chun-Hou Zheng, Ying-Lian Gao:
Heterogeneous network and graph attention auto-encoder for LncRNA-disease association prediction. CoRR abs/2405.02354 (2024) - 2023
- [j20]Zhen-Chang Wang, Jin-Xing Liu, Junliang Shang, Ling-Yun Dai, Chun-Hou Zheng, Juan Wang:
ARGLRR: A Sparse Low-Rank Representation Single-Cell RNA-Sequencing Data Clustering Method Combined with a New Graph Regularization. J. Comput. Biol. 30(8): 848-860 (2023) - [c17]Shuang Wang, Jin-Xing Liu, Bao-Min Liu, Ling-Yun Dai, Feng Li, Ying-Lian Gao:
MKGSAGE: A Computational Framework via Multiple Kernel Fusion on GraphSAGE for Inferring Potential Disease-Related Microbes. BIBM 2023: 648-653 - [c16]Xu Wang, Ling-Yun Dai, Jin-Xing Liu, Shuang Wang:
MLQP: A Machine Learning Based Quadratic Prediction Method for MiRNA-Disease Associations. BIBM 2023: 3208-3211 - [c15]Jie Xu, Juan Wang, Jin-Xing Liu, Junliang Shang, Lingyun Dai, Kuiting Yan, Shasha Yuan:
Epileptic Seizure Detection Based on Feature Extraction and CNN-BiGRU Network with Attention Mechanism. ICIC (2) 2023: 308-319 - [c14]Tian-Jing Qiao, Feng Li, Shasha Yuan, Ling-Yun Dai, Juan Wang:
scGASI: A Graph Autoencoder-Based Single-Cell Integration Clustering Method. ISBRA 2023: 178-189 - 2022
- [j19]Juan Wang, Cong-Hai Lu, Xiang-Zhen Kong, Ling-Yun Dai, Shasha Yuan, Xiaofeng Zhang:
Multi-view manifold regularized compact low-rank representation for cancer samples clustering on multi-omics data. BMC Bioinform. 22-S(12): 334 (2022) - [j18]Han Han, Rong Zhu, Jin-Xing Liu, Ling-Yun Dai:
Predicting miRNA-disease associations via layer attention graph convolutional network model. BMC Medical Informatics Decis. Mak. 22(1): 69 (2022) - [c13]Rong Zhu, Hua-Hui Gao, Junliang Shang, Ling-Yun Dai:
KSMDB: A classification method in imbalanced COVID dataset based on KmeansSMOTE and DeBERT. BIBM 2022: 3242-3247 - [c12]Zeng Zeng, Shenghao Zhao, Qing Da, Peisheng Qian, Tam Wai Leong, Lingyun Dai, Pär Nordlund, Nayana Prabhu, Ziyuan Zhao, Xulei Yang:
CycleDNN - A Novel Deep Neural Network Model for CETSA Feature Prediction cross Cell Lines. EMBC 2022: 1647-1650 - [c11]Xulei Yang, Qing Da, Peisheng Qian, Bharadwaj Veeravalli, Tam Wai Leong, Lingyun Dai, Pär Nordlund, Nayana Prabhu, Ziyuan Zhao, Zeng Zeng:
CETSA Feature Based Clustering for Protein Outlier Discovery by Protein-to-Protein Interaction Prediction. EMBC 2022: 1659-1662 - [c10]Zhen-Chang Wang, Jin-Xing Liu, Junliang Shang, Ling-Yun Dai, Chun-Hou Zheng, Juan Wang:
ARGLRR: An Adjusted Random Walk Graph Regularization Sparse Low-Rank Representation Method for Single-Cell RNA-Sequencing Data Clustering. ISBRA 2022: 126-137 - 2021
- [j17]Rong Zhu, Yong Wang, Jin-Xing Liu, Ling-Yun Dai:
IPCARF: improving lncRNA-disease association prediction using incremental principal component analysis feature selection and a random forest classifier. BMC Bioinform. 22(1): 175 (2021) - [j16]Delu Ma, Shasha Yuan, Junliang Shang, Jin-Xing Liu, Lingyun Dai, Xiangzhen Kong, Fangzhou Xu:
The Automatic Detection of Seizure Based on Tensor Distance And Bayesian Linear Discriminant Analysis. Int. J. Neural Syst. 31(5): 2150006:1-2150006:15 (2021) - [j15]Chuan-Yuan Wang, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Junliang Shang:
Sparse robust graph-regularized non-negative matrix factorization based on correntropy. J. Bioinform. Comput. Biol. 19(1): 2050047:1-2050047:24 (2021) - [j14]Ling-Yun Dai, Jin-Xing Liu, Rong Zhu, Juan Wang, Shasha Yuan:
Logistic Weighted Profile-Based Bi-Random Walk for Exploring MiRNA-Disease Associations. J. Comput. Sci. Technol. 36(2): 276-287 (2021) - [c9]He-Ming Chu, Xiang-Zhen Kong, Jin-Xing Liu, Juan Wang, Shasha Yuan, Ling-Yun Dai:
Joint CC and Bimax: A Biclustering Method for Single-Cell RNA-Seq Data Analysis. ISBRA 2021: 499-510 - 2020
- [j13]Ling-Yun Dai, Rong Zhu, Juan Wang:
Joint Nonnegative Matrix Factorization Based on Sparse and Graph Laplacian Regularization for Clustering and Co-Differential Expression Genes Analysis. Complex. 2020: 3917812:1-3917812:10 (2020) - [j12]Juan Wang, Jin-Xing Liu, Chun-Hou Zheng, Cong-Hai Lu, Ling-Yun Dai, Xiang-Zhen Kong:
Block-Constraint Laplacian-Regularized Low-Rank Representation and Its Application for Cancer Sample Clustering Based on Integrated TCGA Data. Complex. 2020: 4865738:1-4865738:13 (2020) - [c8]Yu Song, Xiang-Zhen Kong, Jin-Xing Liu, Juan Wang, Shasha Yuan, Ling-Yun Dai:
Dual Graph regularized PCA based on Different Norm Constraints for Bi-clustering Analysis on Single-cell RNA-seq Data. BIBM 2020: 92-95 - [c7]Shasha Yuan, Jin-Xing Liu, Junliang Shang, Fangzhou Xu, Lingyun Dai, Xiangzhen Kong:
Automatic Seizure Prediction based on Modified Stockwell Transform and Tensor Decomposition. BIBM 2020: 1503-1509
2010 – 2019
- 2019
- [j11]Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang, Ling-Yun Dai:
The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method. BMC Bioinform. 20(1): 5 (2019) - [j10]Rong Zhu, Guangshun Li, Jin-Xing Liu, Ling-Yun Dai, Ying Guo:
ACCBN: ant-Colony-clustering-based bipartite network method for predicting long non-coding RNA-protein interactions. BMC Bioinform. 20(1): 16 (2019) - [j9]Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Shasha Yuan:
L2, 1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions. BMC Bioinform. 20-S(8): 287:1-287:13 (2019) - [j8]Chun-Mei Feng, Yong Xu, Mi-Xiao Hou, Ling-Yun Dai, Junliang Shang:
PCA via joint graph Laplacian and sparse constraint: Identification of differentially expressed genes and sample clustering on gene expression data. BMC Bioinform. 20-S(22): 716 (2019) - [j7]Juan Wang, Cong-Hai Lu, Jin-Xing Liu, Ling-Yun Dai, Xiang-Zhen Kong:
Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints. BMC Bioinform. 20-S(22): 718 (2019) - [j6]Mi-Xiao Hou, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Xiang-Zhen Kong, Junliang Shang:
Network analysis based on low-rank method for mining information on integrated data of multi-cancers. Comput. Biol. Chem. 78: 468-473 (2019) - [j5]Ling-Yun Dai, Chun-Hou Zheng, Jin-Xing Liu, Rong Zhu, Shasha Yuan, Juan Wang, Xiang-Zhen Kong:
Integrative graph regularized matrix factorization for drug-pathway associations analysis. Comput. Biol. Chem. 78: 474-480 (2019) - [j4]Juan Wang, Jin-Xing Liu, Xiang-Zhen Kong, Shasha Yuan, Ling-Yun Dai:
Laplacian regularized low-rank representation for cancer samples clustering. Comput. Biol. Chem. 78: 504-509 (2019) - [j3]Yong-Jing Hao, Ying-Lian Gao, Mi-Xiao Hou, Ling-Yun Dai, Jin-Xing Liu:
Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection. Complex. 2019: 7081674:1-7081674:12 (2019) - 2018
- [c6]Ling-Yun Dai, Jin-Xing Liu, Rong Zhu, Xiang-Zhen Kong, Mi-Xiao Hou, Shasha Yuan:
Sparse Orthogonal Nonnegative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Tumor Samples. BIBM 2018: 1332-1337 - [c5]Rong Zhu, Guangshun Li, Jin-Xing Liu, Ling-Yun Dai, Shasha Yuan, Ying Guo:
A Fast Quantum Clustering Approach for Cancer Gene Clustering. BIBM 2018: 1610-1613 - [c4]Mi-Xiao Hou, Jin-Xing Liu, Junliang Shang, Ying-Lian Gao, Xiang-Zhen Kong, Ling-Yun Dai:
Performance Analysis of Non-negative Matrix Factorization Methods on TCGA Data. ICIC (2) 2018: 407-418 - 2017
- [j2]Ling-Yun Dai, Chun-Mei Feng, Jin-Xing Liu, Chun-Hou Zheng, Jiguo Yu, Mi-Xiao Hou:
Robust Nonnegative Matrix Factorization via Joint Graph Laplacian and Discriminative Information for Identifying Differentially Expressed Genes. Complex. 2017: 4216797:1-4216797:11 (2017) - [j1]Xiu-Xiu Xu, Ying-Lian Gao, Jin-Xing Liu, Yaxuan Wang, Ling-Yun Dai, Xiang-Zhen Kong, Shasha Yuan:
A novel low-rank representation method for identifying differentially expressed genes. Int. J. Data Min. Bioinform. 19(3): 185-201 (2017) - [c3]Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Ling-Yun Dai:
Low-rank representation regularized by L2, 1-norm for identifying differentially expressed genes. BIBM 2017: 626-629 - [c2]Ling-Yun Dai, Jin-Xing Liu, Chun-Hou Zheng, Junliang Shang, Chun-Mei Feng, Yaxuan Wang:
Robust graph regularized sparse orthogonal nonnegative matrix factorization for identifying differentially expressed genes. BIBM 2017: 1900-1905 - 2016
- [c1]Ling-Yun Dai, Chun-Mei Feng, Jin-Xing Liu, Chun-Hou Zheng, Mi-Xiao Hou, Jiguo Yu:
Robust graph regularized discriminative nonnegative matrix factorization for characteristic gene selection. BIBM 2016: 1253-1258
Coauthor Index
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last updated on 2024-11-04 21:38 CET by the dblp team
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