A Novel Algorithm for Handwritten Chinese Character Recognition. - Feng Qi; Minghua Deng; Minping Qian; Xueqing Zhu (ICMI, 2000)

Inferring domain-domain interactions from protein-protein interactions. - Minghua Deng; Shipra Mehta; Fengzhu Sun; Ting Chen 006 (RECOMB, 2002)

Assessment of the reliability of protein-protein interactions and protein function prediction. - Minghua Deng; Fengzhu Sun; Ting Chen 006 (Pacific Symposium on Biocomputing, 2003)

Prediction of Protein Function Using Protein-Protein Interaction Data. - Minghua Deng; Kui Zhang; Shipra Mehta; Ting Chen 006; Fengzhu Sun (J. Comput. Biol., 2003)

Kernel-Based Data Fusion and Its Application to Protein Function Prediction in Yeast. - Gert R. G. Lanckriet; Minghua Deng; Nello Cristianini; Michael I. Jordan; William Stafford Noble (Pacific Symposium on Biocomputing, 2004)

An Improvement for Eulerian Path of Assembly. - Shenglan Peng; Minghua Deng; Minping Qian (SNPD, 2004)

Mapping gene ontology to proteins based on protein-protein interaction data. - Minghua Deng; Zhidong Tu; Fengzhu Sun; Ting Chen 006 (Bioinform., 2004)

An Integrated Probabilistic Model for Functional Prediction of Proteins. - Minghua Deng; Ting Chen 006; Fengzhu Sun (J. Comput. Biol., 2004)

Using a Stochastic AdaBoost Algorithm to Discover Interactome Motif Pairs from Sequences. - Huan Yu; Minping Qian; Minghua Deng (ICIC (3), 2006)

Nonequilibrium Model for Yeast Cell Cycle. - Yuping Zhang; Huan Yu; Minghua Deng; Minping Qian (ICIC (3), 2006)

An integrated approach to the prediction of domain-domain interactions. - Hyunju Lee; Minghua Deng; Fengzhu Sun; Ting Chen 006 (BMC Bioinform., 2006)

On Design of Oligonucleotide SNP Arrays and Methods for Genotype Calling. - Wenjiang J. Fu; Ming Li 065; Lin Wan; Minghua Deng; Minping Qian (BMEI (1), 2008)

A Method to Correct Systematic Bias in Affymetrix SNP Arrays. - Lin Wan; Wenjiang J. Fu; Minghua Deng; Minping Qian (BMEI (1), 2008)

A Robust Empirical Bayesian Method for Detecting Differentially Expressed Genes. - Fugui Wang; Lin Hou; Jiangfeng Xu; Minping Qian; Minghua Deng (BMEI, 2009)

The Implementation and Application of the Microarray Preprocessing Generalized PDNN Model. - Wei Wei; Lin Wan; Minping Qian; Minghua Deng (BMEI, 2009)

Pathway Detection Based on Hierarchical LASSO Regression Model. - Hao Zheng; Fugui Wang; Jiangfeng Xu; Nengfeng Zhou; Minping Qian; Ji Zhu; Minghua Deng (BMEI, 2009)

Feature-Based Causal Structure Discovery in Protein and Gene Expression Data with Bayesian Network. - Jingwei Liu; Minghua Deng; Minping Qian (ICNC (2), 2009)

Searching for bidirectional promoters in Arabidopsis thaliana. - Quan Wang 004; Lin Wan; Dayong Li; Lihuang Zhu; Minping Qian; Minghua Deng (BMC Bioinform., 2009)

REMAS: a new regression model to identify alternative splicing events from exon array data. - Hao Zheng; Xingyi Hang; Ji Zhu; Minping Qian; Wubin Qu; Chenggang Zhang; Minghua Deng (BMC Bioinform., 2009)

A hybridization model for tiling array analysis. - Quan Wang 004; Linbo Wang; Minping Qian; Minghua Deng (BIBM Workshops, 2010)

Combinatorial regulation of transcription factors and microRNAs. - Naifang Su; Yufu Wang; Minping Qian; Minghua Deng (BMC Syst. Biol., 2010)

The Biases of Copy Numbers from Affymetrix SNP Arrays and Their Corrections. - Quan Chen; Minghua Deng; Minping Qian; Lin Wan; Yi Xiao (Commun. Inf. Syst., 2010)

Binding Energy Landscape Analysis Helps to Discriminate True Hits from High-Scoring Decoys in Virtual Screening. - Dengguo Wei; Hao Zheng; Naifang Su; Minghua Deng; Luhua Lai (J. Chem. Inf. Model., 2010)

Reverse Engineering of Gene Regulation Networks with an Application to the DREAM4 in silico Network Challenge. - Hyonho Chun; Jia Kang; Xianghua Zhang; Minghua Deng; Haisu Ma; Hongyu Zhao 003 (Handbook of Statistical Bioinformatics, 2011)

Modular analysis of the probabilistic genetic interaction network. - Lin Hou; Lin Wang; Minping Qian; Dong Li 018; Chao Tang; Yunping Zhu; Minghua Deng; Fangting Li (Bioinform., 2011)

A Lasso regression model for the construction of microRNA-target regulatory networks. - Yiming Lu; Yang Zhou; Wubin Qu; Minghua Deng; Chenggang Zhang (Bioinform., 2011)

Integrating multiple types of data to predict novel cell cycle-related genes. - Lin Wang; Lin Hou; Minping Qian; Fangting Li; Minghua Deng (BMC Syst. Biol., 2011)

Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads: Extended Abstract. - Kai Song; Jie Ren 006; Zhiyuan Zhai; Xuemei Liu; Minghua Deng; Fengzhu Sun (RECOMB, 2012)

Multiple alignment-free sequence comparison. - Jie Ren 006; Kai Song; Fengzhu Sun; Minghua Deng; Gesine Reinert (Bioinform., 2013)

Alignment-Free Sequence Comparison Based on Next-Generation Sequencing Reads. - Kai Song; Jie Ren 006; Zhiyuan Zhai; Xuemei Liu; Minghua Deng; Fengzhu Sun (J. Comput. Biol., 2013)

New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing. - Kai Song; Jie Ren 006; Gesine Reinert; Minghua Deng; Michael S. Waterman; Fengzhu Sun (Briefings Bioinform., 2014)

CCLasso: correlation inference for compositional data through Lasso. - Huaying Fang; Chengcheng Huang; Hongyu Zhao 003; Minghua Deng (Bioinform., 2015)

Estimation of isoform expression in RNA-seq data using a hierarchical Bayesian model. - Zengmiao Wang; Jun Wang; Changjing Wu; Minghua Deng (J. Bioinform. Comput. Biol., 2015)

Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics. - Jie Ren 006; Kai Song; Minghua Deng; Gesine Reinert; Charles H. Cannon; Fengzhu Sun (Bioinform., 2016)

A network based covariance test for detecting multivariate eQTL in saccharomyces cerevisiae. - Huili Yuan; Zhenye Li; Nelson L. S. Tang; Minghua Deng (BMC Syst. Biol., 2016)

VCNet: vector-based gene co-expression network construction and its application to RNA-seq data. - Zengmiao Wang; Huaying Fang; Nelson L. S. Tang; Minghua Deng (Bioinform., 2017)

SVmine improves structural variation detection by integrative mining of predictions from multiple algorithms. - Yuchao Xia; Yun Liu; Minghua Deng; Ruibin Xi (Bioinform., 2017)

Pysim-sv: a package for simulating structural variation data with GC-biases. - Yuchao Xia; Yun Liu; Minghua Deng; Ruibin Xi (BMC Bioinform., 2017)

gCoda: Conditional Dependence Network Inference for Compositional Data. - Huaying Fang; Chengcheng Huang; Hongyu Zhao 003; Minghua Deng (J. Comput. Biol., 2017)

RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning. - Yujuan Gao; Sheng Wang 001; Minghua Deng; Jinbo Xu (BMC Bioinform., 2018)

Compositional data network analysis via lasso penalized D-trace loss. - Huili Yuan; Shun He; Minghua Deng (Bioinform., 2019)

Predicting protein inter-residue contacts using composite likelihood maximization and deep learning. - Haicang Zhang; Qi Zhang; Fusong Ju; Jianwei Zhu; Yujuan Gao; Ziwei Xie; Minghua Deng; Shiwei Sun; Wei-Mou Zheng; Dongbo Bu (BMC Bioinform., 2019)

Correction to: Predicting protein inter-residue contacts using composite likelihood maximization and deep learning. - Haicang Zhang; Qi Zhang; Fusong Ju; Jianwei Zhu; Yujuan Gao; Ziwei Xie; Minghua Deng; Shiwei Sun; Wei-Mou Zheng; Dongbo Bu (BMC Bioinform., 2019)

Network Clustering Analysis Using Mixture Exponential-Family Random Graph Models and Its Application in Genetic Interaction Data. - Yishu Wang 003; Huaying Fang; Dejie Yang; Hongyu Zhao 003; Minghua Deng (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

scRMD: imputation for single cell RNA-seq data via robust matrix decomposition. - Chong Chen 002; Changjing Wu; Linjie Wu; Xiaochen Wang; Minghua Deng; Ruibin Xi (Bioinform., 2020)

Expectation pooling: an effective and interpretable pooling method for predicting DNA-protein binding. - Xiao Luo 001; Xinming Tu; Yang Ding; Ge Gao; Minghua Deng (Bioinform., 2020)

A Survey on Deep Hashing Methods. - Xiao Luo 001; Chong Chen 002; Huasong Zhong; Hao Zhang; Minghua Deng; Jianqiang Huang; Xiansheng Hua 001 (CoRR, 2020)

CIMON: Towards High-quality Hash Codes. - Xiao Luo 001; Daqing Wu; Zeyu Ma 001; Chong Chen 002; Huasong Zhong; Minghua Deng; Jianqiang Huang; Xian-Sheng Hua 001 (CoRR, 2020)

Direct interaction network inference for compositional data via codaloss. - Liang Chen; Shun He; Yuyao Zhai; Minghua Deng (J. Bioinform. Comput. Biol., 2020)

International Workshop on Applications of Probability and Statistics to Biology, July 11-13, 2019. - Minghua Deng; Jianfeng Feng; Hong Qian; Lin Wan; Fengzhu Sun (Quant. Biol., 2020)

Graph Contrastive Clustering. - Huasong Zhong; Jianlong Wu; Chong Chen 002; Jianqiang Huang; Minghua Deng; Liqiang Nie; Zhouchen Lin; Xian-Sheng Hua 001 (ICCV, 2021)

Composition-Enhanced Graph Collaborative Filtering for Multi-behavior Recommendation. - Daqing Wu; Xiao Luo 001; Zeyu Ma 001; Chong Chen 002; Pengfei Wang 008; Minghua Deng; Jinwen Ma (ICDM, 2021)

DNA-GCN: Graph Convolutional Networks for Predicting DNA-Protein Binding. - Yuhang Guo 002; Xiao Luo 001; Liang Chen; Minghua Deng (ICIC (3), 2021)

Deep Unsupervised Hashing by Distilled Smooth Guidance. - Xiao Luo 001; Zeyu Ma 001; Daqing Wu; Huasong Zhong; Chong Chen 002; Jinwen Ma; Minghua Deng (ICME, 2021)

Deep Unsupervised Hashing by Global and Local Consistency. - Xiao Luo 001; Daqing Wu; Chong Chen 002; Jinwen Ma; Minghua Deng (ICME, 2021)

Deep Supervised Hashing by Classification for Image Retrieval. - Xiao Luo 001; Yuhang Guo 002; Zeyu Ma 001; Huasong Zhong; Tao Li 040; Wei Ju 001; Chong Chen 002; Minghua Deng (ICONIP (4), 2021)

Concordant Contrastive Learning for Semi-supervised Node Classification on Graph. - Daqing Wu; Xiao Luo 001; Xiangyang Guo; Chong Chen 002; Minghua Deng; Jinwen Ma (ICONIP (1), 2021)

An Interpretation of Convolutional Neural Networks for Motif Finding from the View of Probability. - Weinan Wang; Yuhang Guo 002; Wei Ju 001; Xiao Luo 001; Minghua Deng (ICTAI, 2021)

CIMON: Towards High-quality Hash Codes. - Xiao Luo 001; Daqing Wu; Zeyu Ma 001; Chong Chen 002; Minghua Deng; Jinwen Ma; Zhongming Jin 001; Jianqiang Huang; Xian-Sheng Hua 001 (IJCAI, 2021)

ARGO: Modeling Heterogeneity in E-commerce Recommendation. - Daqing Wu; Xiao Luo 001; Zeyu Ma 001; Chong Chen 002; Minghua Deng; Jinwen Ma (IJCNN, 2021)

A Statistical Approach to Mining Semantic Similarity for Deep Unsupervised Hashing. - Xiao Luo 001; Daqing Wu; Zeyu Ma 001; Chong Chen 002; Minghua Deng; Jianqiang Huang; Xian-Sheng Hua 001 (ACM Multimedia, 2021)

Single-cell RNA-seq data semi-supervised clustering and annotation via structural regularized domain adaptation. - Liang Chen; Qiuyan He; Yuyao Zhai; Minghua Deng (Bioinform., 2021)

Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation. - Xiao Luo 001; Daqing Wu; Chong Chen 002; Jinwen Ma; Minghua Deng; Chen Shen 003; Jianqiang Huang; Xian-Sheng Hua 001 (CoRR, 2021)

Mutual Nearest Neighbor Contrast and Hybrid Prototype Self-Training for Universal Domain Adaptation. - Liang Chen; Qianjin Du; Yihang Lou; Jianzhong He; Tao Bai; Minghua Deng (AAAI, 2022)

Evidential Neighborhood Contrastive Learning for Universal Domain Adaptation. - Liang Chen; Yihang Lou; Jianzhong He; Tao Bai; Minghua Deng (AAAI, 2022)

Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation. - Shengsen Wu; Liang Chen; Yihang Lou; Yan Bai; Tao Bai; Minghua Deng; Ling-Yu Duan (AAAI, 2022)

Geometric Anchor Correspondence Mining with Uncertainty Modeling for Universal Domain Adaptation. - Liang Chen; Yihang Lou; Jianzhong He; Tao Bai; Minghua Deng (CVPR, 2022)

DHWP: Learning High-Quality Short Hash Codes Via Weight Pruning. - Zeyu Ma 001; Yuhang Guo 002; Xiao Luo 001; Chong Chen 002; Minghua Deng; Wei Cheng 002; Guangming Lu 002 (ICASSP, 2022)

DualGraph: Improving Semi-supervised Graph Classification via Dual Contrastive Learning. - Xiao Luo 001; Wei Ju 001; Meng Qu; Chong Chen 002; Minghua Deng; Xian-Sheng Hua 001; Ming Zhang 004 (ICDE, 2022)

TGNN: A Joint Semi-supervised Framework for Graph-level Classification. - Wei Ju 001; Xiao Luo 001; Meng Qu; Yifan Wang 014; Chong Chen 002; Minghua Deng; Xian-Sheng Hua 001; Ming Zhang 004 (IJCAI, 2022)

Improved Deep Unsupervised Hashing with Fine-grained Semantic Similarity Mining for Multi-Label Image Retrieval. - Zeyu Ma 001; Xiao Luo 001; Yingjie Chen; Mixiao Hou; Jinxing Li; Minghua Deng; Guangming Lu 002 (IJCAI, 2022)

Rare variant association tests for ancestry-matched case-control data based on conditional logistic regression. - Shanshan Cheng; Jingjing Lyu; Xian Shi; Kai Wang; Zengmiao Wang; Minghua Deng; Baoluo Sun; Chaolong Wang (Briefings Bioinform., 2022)

scNAME: neighborhood contrastive clustering with ancillary mask estimation for scRNA-seq data. - Hui Wan; Liang Chen; Minghua Deng (Bioinform., 2022)

scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasets. - Musu Yuan; Liang Chen; Minghua Deng (Bioinform., 2022)

Statistical Methods for Microbiome Compositional Data Network Inference: A Survey. - Liang Chen; Hui Wan; Qiuyan He; Shun He; Minghua Deng (J. Comput. Biol., 2022)

Uncovering the Dominant Motion Modes of Allosteric Regulation Improves Allosteric Site Prediction. - Juan Xie; Shiwei Wang; Youjun Xu; Minghua Deng; Luhua Lai (J. Chem. Inf. Model., 2022)

GHNN: Graph Harmonic Neural Networks for semi-supervised graph-level classification. - Wei Ju 001; Xiao Luo 001; Zeyu Ma 001; Junwei Yang; Minghua Deng; Ming Zhang 004 (Neural Networks, 2022)

Profiling transcription factor activity dynamics using intronic reads in time-series transcriptome data. - Yan Wu; Lingfeng Xue; Wen Huang; Minghua Deng; Yihan Lin (PLoS Comput. Biol., 2022)

Improve Deep Unsupervised Hashing via Structural and Intrinsic Similarity Learning. - Xiao Luo 001; Zeyu Ma 001; Wei Cheng 002; Minghua Deng (IEEE Signal Process. Lett., 2022)

scEMAIL: Universal and Source-free Annotation Method for scRNA-seq Data with Novel Cell-type Perception. - Hui Wan; Liang Chen; Minghua Deng (Genom. Proteom. Bioinform., 2022)

Generalized Cell Type Annotation and Discovery for Single-Cell RNA-Seq Data. - Yuyao Zhai; Liang Chen; Minghua Deng (AAAI, 2023)

Realistic Cell Type Annotation and Discovery for Single-cell RNA-seq Data. - Yuyao Zhai; Liang Chen; Minghua Deng (IJCAI, 2023)

Clustering single-cell multi-omics data with MoClust. - Musu Yuan; Liang Chen; Minghua Deng (Bioinform., 2023)

A Survey on Deep Hashing Methods. - Xiao Luo 001; Haixin Wang 003; Daqing Wu; Chong Chen 002; Minghua Deng; Jianqiang Huang; Xian-Sheng Hua 001 (ACM Trans. Knowl. Discov. Data, 2023)

scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery. - Yuyao Zhai; Liang Chen; Minghua Deng (Briefings Bioinform., 2023)

Distribution-Independent Cell Type Identification for Single-Cell RNA-seq Data. - Yuyao Zhai; Liang Chen; Minghua Deng (IJCAI, 2024)

scPLAN: a hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinement. - Qirui Guo; Musu Yuan; Lei Zhang; Minghua Deng (Briefings Bioinform., 2024)

Continually adapting pre-trained language model to universal annotation of single-cell RNA-seq data. - Hui Wan; Musu Yuan; Yiwei Fu; Minghua Deng (Briefings Bioinform., 2024)

scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data. - Yuyao Zhai; Liang Chen; Minghua Deng (Briefings Bioinform., 2024)

Intrinsic structure exploitation with dual alignment for universal visual recognition. - Yuyao Zhai; Liang Chen; Minghua Deng (Knowl. Based Syst., 2024)

SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data. - Musu Yuan; Hui Wan; Zihao Wang; Qirui Guo; Minghua Deng (Briefings Bioinform., 2024)

scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq data. - Yuyao Zhai; Liang Chen; Minghua Deng (Briefings Bioinform., 2024)

Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation. - Xiao Luo 001; Daqing Wu; Yiyang Gu; Chong Chen 002; Luchen Liu; Jinwen Ma; Ming Zhang 004; Minghua Deng; Jianqiang Huang; Xian-Sheng Hua 001 (ACM Trans. Knowl. Discov. Data, 2024)

CLEAR: Cluster-Enhanced Contrast for Self-Supervised Graph Representation Learning. - Xiao Luo 001; Wei Ju 001; Meng Qu; Yiyang Gu; Chong Chen 002; Minghua Deng; Xian-Sheng Hua 001; Ming Zhang 004 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Improving tree probability estimation with stochastic optimization and variance reduction. - Tianyu Xie 001; Musu Yuan; Minghua Deng; Cheng Zhang (Stat. Comput., 2024)

Gradient-Based Sample Selection for Black-Box Universal Domain Adaptation. - Qiuyan He; Minghua Deng (AAAI, 2025)

MARK: Multi-agent Collaboration with Ranking Guidance for Text-attributed Graph Clustering. - Yiwei Fu; Yuxing Zhang; Chunchun Chen; JianwenMa JianwenMa; Quan Yuan; Rong-Cheng Tu; Xinli Huang; Wei Ye; Xiao Luo 001; Minghua Deng (ACL (Findings), 2025)

Semi-supervised contrastive learning variational autoencoder Integrating single-cell multimodal mosaic datasets. - Zihao Wang; Zeyu Wu; Minghua Deng (BMC Bioinform., 2025)