C. Liang

发表

GLNMDA: a novel method for miRNA-disease association prediction based on global linear neighborhoods

Jia-wei Luo, Qiu Xiao, Shengpeng Yu, 2018, RNA biology.

An in-silico method with graph-based multi-label learning for large-scale predicting circRNA-disease associations.

Jiancheng Zhong, Qiu Xiao, Jiawei Luo, 2020, Genomics.

Network simulation reveals significant contribution of network motifs to the age-dependency of yeast protein-protein interaction networks.

Jiawei Luo, C. Liang, Dan Song, 2014, Molecular bioSystems.

MOEPGA: A novel method to detect protein complexes in yeast protein-protein interaction networks based on MultiObjective Evolutionary Programming Genetic Algorithm

Cheng Liang, Dan Song, Shulin Wang, 2015, Comput. Biol. Chem..

Inferring Disease–miRNA Associations by Self-Weighting with Multiple Data Source

C. Liang, X. Y. Yang, L. Gao, 2018, Molecular Biology.

Integrating Functional and Topological Properties to Identify Biological Network Motif in Protein Interaction Networks

Cheng Liang, Dan Song, Jiawei Luo, 2014 .

Heterodimeric DNA motif synthesis and validations

You-Qiang Song, Ka-chun Wong, Qiuzhen Lin, 2018, Nucleic acids research.

Model the evolution of protein interaction network assisted with protein age.

Cheng Liang, Dan Song, Jiawei Luo, 2013, Journal of theoretical biology.

Investigating the functional implications of reinforcing feedback loops in transcriptional regulatory networks.

S. Easterbrook, Zhaolei Zhang, Yue Li, 2014, Molecular bioSystems.

Predicting miRNA-disease associations based on graph attention network with multi-source information

Qiu Xiao, Jiawei Luo, C. Liang, 2022, BMC Bioinformatics.

CombiMotif: A new algorithm for network motifs discovery in protein–protein interaction networks

Jiawei Luo, C. Liang, Guanghui Li, 2014 .

GGAECDA: Predicting circRNA-disease associations using graph autoencoder based on graph representation learning

Qiu Xiao, Jiawei Luo, C. Liang, 2022, Comput. Biol. Chem..

DNA Sequencing Technologies

Ka-Chun Wong, Sam Kwong, Jiao Zhang, 2019, ACM Comput. Surv..

MCLPMDA: A novel method for miRNA‐disease association prediction based on matrix completion and label propagation

Cheng Liang, Qiu Xiao, Sheng-Peng Yu, 2018, Journal of cellular and molecular medicine.

Semi-supervised prediction of human miRNA-disease association based on graph regularization framework in heterogeneous networks

Cheng Liang, Jiawei Luo, Pingjian Ding, 2018, Neurocomputing.

Collective Prediction of Disease-Associated miRNAs Based on Transduction Learning

Cheng Liang, Jiawei Luo, Pingjian Ding, 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity

Cheng Liang, Jiawei Luo, Qiu Xiao, 2018, J. Biomed. Informatics.

Inferring probabilistic miRNA–mRNA interaction signatures in cancers: a role-switch approach

Cheng Liang, Zhaolei Zhang, Ka-Chun Wong, 2014, Nucleic acids research.

Multi-view Unsupervised Feature Selection via Consensus Guided Low-rank Tensor Learning

C. Liang, Lianzhi Wang, Wenjiao Dong, 2022, 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A novel semi-supervised model for miRNA-disease association prediction based on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{d

Cheng Liang, Ka-Chun Wong, Jiawei Luo, 2018, Journal of Translational Medicine.

SNMDA: A novel method for predicting microRNA‐disease associations based on sparse neighbourhood

Cheng Liang, Huaxiang Zhang, Jiawei Luo, 2018, Journal of cellular and molecular medicine.

Inferring Disease–miRNA Associations by Self-Weighting with Multiple Data Source

X Y Yang, L Gao, С Liang, 2018, Molecular Biology.

Early Cancer Detection from Multianalyte Blood Test Results

Jun Yu, S. Kwong, Ka-chun Wong, 2019, iScience.

A graph regularized non-negative matrix factorization method for identifying microRNA-disease associations

Cheng Liang, Jiawei Luo, Jie Cai, 2018, Bioinform..

Prediction of microRNA–disease associations with a Kronecker kernel matrix dimension reduction model

Cheng Liang, Guanghui Li, Qiu Xiao, 2018 .

Multiview Consensus Graph Learning for lncRNA–Disease Association Prediction

Cheng Liang, Qiu Xiao, Pingjian Ding, 2020, Frontiers in Genetics.

Prediction of disease-miRNA associations by walking on a bipartite network

Cheng Liang, Ling Gao, Xiaoying Yang, 2017, 2017 Chinese Automation Congress (CAC).

Multiple Protein Subcellular Locations Prediction Based on Deep Convolutional Neural Networks with Self-Attention Mechanism

C. Liang, Yi Cao, Hanhan Cong, 2022, Interdisciplinary Sciences: Computational Life Sciences.

NCPCDA: network consistency projection for circRNA–disease association prediction

Cheng Liang, Jiawei Luo, Qiu Xiao, 2019, RSC advances.

Cancer subtype identification by consensus guided graph autoencoders

Jiawei Luo, Cheng Liang, Mingchao Shang, 2021, Bioinform..

Incorporating Multisource Knowledge To Predict Drug Synergy Based on Graph Co-regularization

Cheng Liang, Jiawei Luo, Cong Shen, 2019, J. Chem. Inf. Model..

Self-Weighted Multi-Kernel Multi-Label Learning for Potential miRNA-Disease Association Prediction

Cheng Liang, Huaxiang Zhang, Jiawei Luo, 2019, Molecular therapy. Nucleic acids.

A Novel Method to Detect Functional microRNA Regulatory Modules by Bicliques Merging

Cheng Liang, Yue Li, Jiawei Luo, 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Prediction of lncRNA-disease associations based on robust multi-label learning

Quanmeng Sun, Jiaxin Zhang, Cheng Liang, 2021, Current Bioinformatics.

Predicting MicroRNA-Disease Associations Using Network Topological Similarity Based on DeepWalk

Cheng Liang, Jiawei Luo, Qiu Xiao, 2017, IEEE Access.

Prediction of LncRNA-Disease Associations Based on Network Consistency Projection

Yuejin Zhang, Jiawei Luo, Qiu Xiao, 2019, IEEE Access.

Using Graph Attention Network and Graph Convolutional Network to Explore Human CircRNA–Disease Associations Based on Multi-Source Data

Qiu Xiao, Jiawei Luo, C. Liang, 2022, Frontiers in Genetics.

Potential circRNA-disease association prediction using DeepWalk and network consistency projection

Cheng Liang, Jiawei Luo, Hailin Chen, 2020, J. Biomed. Informatics.

Identifying lncRNA and mRNA Co-Expression Modules from Matched Expression Data in Ovarian Cancer

Cheng Liang, Qiu Xiao, Guanghui Li, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

CeModule: an integrative framework for discovering regulatory patterns from genomic data in cancer

Cheng Liang, Jiawei Luo, Jie Cai, 2019, BMC Bioinformatics.

Mirsynergy: detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion

Cheng Liang, Zhaolei Zhang, Yue Li, 2014, Bioinform..

Robust optimal graph clustering

Cheng Liang, Jingjing Li, Fei Wang, 2020, Neurocomputing.

Multi-view feature selection via Nonnegative Structured Graph Learning

Jingjing Li, Lei Zhu, Xiushan Nie, 2020, Neurocomputing.

A knowledge-driven network for fine-grained relationship detection between miRNA and disease

Jiawei Luo, Shengpeng Yu, C. Liang, 2022, Briefings Bioinform..

KATZMDA: Prediction of miRNA-Disease Associations Based on KATZ Model

Cheng Liang, Huaxiang Zhang, Yu Qu, 2018, IEEE Access.

Human disease MiRNA inference by combining target information based on heterogeneous manifolds

Cheng Liang, Jiawei Luo, Qiu Xiao, 2018, J. Biomed. Informatics.

Probabilistic Inference on Multiple Normalized Genome-Wide Signal Profiles With Model Regularization

Cheng Liang, Ka-Chun Wong, Chengbin Peng, 2017, IEEE Transactions on NanoBioscience.

Ka-chun Wong, Jiawei Luo, Shengpeng Yu, 2018, Journal of Translational Medicine.

Inferring Disease–miRNA Associations by Self-Weighting with Multiple Data Source

C. Liang, X. Y. Yang, L. Gao, 2018, Molecular Biology.

Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs

Cheng Liang, Jiawei Luo, Shengpeng Yu, 2019, PLoS Comput. Biol..

MTMO: an efficient network-centric algorithm for subtree counting and enumeration

Cheng Liang, Zheng Xiao, Guanghui Li, 2018, Quantitative Biology.

A novel motif-discovery algorithm to identify co-regulatory motifs in large transcription factor and microRNA co-regulatory networks in human

Cheng Liang, Zhaolei Zhang, Yue Li, 2015, Bioinform..

An Efficient Network Motif Discovery Approach for Co-Regulatory Networks

Cheng Liang, Jiawei Luo, Nguyen Hoang Tu, 2018, IEEE Access.

Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks.

C. Liang, Yahui Long, Xuejing Shi, 2023, Briefings in Bioinformatics.

EMPPNet: Enhancing Molecular Property Prediction via Cross-modal Information Flow and Hierarchical Attention

Hong Wang, C. Liang, Yanshen Sun, 2023, Expert Systems with Applications.

Incomplete multi-view clustering by simultaneously learning robust representations and optimal graph structures

Jiawei Luo, C. Liang, Huaxiang Zhang, 2023, Inf. Sci..

CasANGCL: pre-training and fine-tuning model based on cascaded attention network and graph contrastive learning for molecular property prediction

Shengpeng Yu, C. Liang, Tianyu Liu, 2023, Briefings Bioinform..

A Novel Group Wise-Based Method for Calculating Human miRNA Functional Similarity

Cheng Liang, Jiawei Luo, Ying Liu, 2017, IEEE Access.

A Novel Information Theory-Based Ensemble Feature Selection Framework for High-Dimensional Microarray Data

Cheng Liang, Jie Cai, Jiawei Luo, 2017 .

Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs

Jiawei Luo, Shengpeng Yu, C. Liang, 2019, PLoS Comput. Biol..

A visual representation for RNA secondary structure and its application

Renfa Li, Jiawei Luo, C. Liang, 2012 .

Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction

C. Liang, Guanghui Li, Jiawei Luo, 2024, BMC genomics.

Identifying virulence factors using graph transformer autoencoder with ESMFold-predicted structures

C. Liang, Peihao Bai, Guanghui Li, 2024, Comput. Biol. Medicine.

Self-Weighted Multi-Kernel Multi-Label Learning for Potential miRNA-Disease Association Prediction

Qiu Xiao, Jiawei Luo, C. Liang, 2019, Molecular therapy. Nucleic acids.

Predicting MicroRNA-Disease Associations Using Kronecker Regularized Least Squares Based on Heterogeneous Omics Data

Cheng Liang, Jiawei Luo, Qiu Xiao, 2017, IEEE Access.

A Novel Method to Detect Functional microRNA Regulatory Modules by Bicliques Merging

Yue Li, Jiawei Luo, C. Liang, 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.