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2020 – today
- 2024
[j52]Musu Yuan, Hui Wan, Zihao Wang, Qirui Guo, Minghua Deng
:
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data. Briefings Bioinform. 25(2) (2024)- [j51]Yuyao Zhai, Liang Chen, Minghua Deng:
scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq data. Briefings Bioinform. 25(2) (2024) - [j50]Qirui Guo, Musu Yuan, Lei Zhang, Minghua Deng:
scPLAN: a hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinement. Briefings Bioinform. 25(4) (2024) - [j49]Yuyao Zhai, Liang Chen, Minghua Deng:
Intrinsic structure exploitation with dual alignment for universal visual recognition. Knowl. Based Syst. 300: 112156 (2024) - [j48]Tianyu Xie, Musu Yuan, Minghua Deng, Cheng Zhang:
Improving tree probability estimation with stochastic optimization and variance reduction. Stat. Comput. 34(6): 186 (2024) - [j47]Xiao Luo, Daqing Wu, Yiyang Gu, Chong Chen, Luchen Liu, Jinwen Ma, Ming Zhang, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua:
Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation. ACM Trans. Knowl. Discov. Data 18(1): 14:1-14:26 (2024) - [j46]Xiao Luo, Wei Ju, Meng Qu, Yiyang Gu, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
CLEAR: Cluster-Enhanced Contrast for Self-Supervised Graph Representation Learning. IEEE Trans. Neural Networks Learn. Syst. 35(1): 899-912 (2024) - [c39]Yuyao Zhai, Liang Chen, Minghua Deng:
Distribution-Independent Cell Type Identification for Single-Cell RNA-seq Data. IJCAI 2024: 6143-6151 - 2023
- [j45]Yuyao Zhai, Liang Chen, Minghua Deng:
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery. Briefings Bioinform. 24(2) (2023) - [j44]Musu Yuan, Liang Chen, Minghua Deng:
Clustering single-cell multi-omics data with MoClust. Bioinform. 39(1) (2023) - [j43]Xiao Luo, Haixin Wang, Daqing Wu, Chong Chen, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua:
A Survey on Deep Hashing Methods. ACM Trans. Knowl. Discov. Data 17(1): 15:1-15:50 (2023) - [c38]Yuyao Zhai, Liang Chen, Minghua Deng:
Generalized Cell Type Annotation and Discovery for Single-Cell RNA-Seq Data. AAAI 2023: 5402-5410 - [c37]Yuyao Zhai, Liang Chen, Minghua Deng:
Realistic Cell Type Annotation and Discovery for Single-cell RNA-seq Data. IJCAI 2023: 4967-4974 - [i10]Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
TGNN: A Joint Semi-supervised Framework for Graph-level Classification. CoRR abs/2304.11688 (2023) - 2022
- [j42]Shanshan Cheng, Jingjing Lyu, Xian Shi, Kai Wang, Zengmiao Wang, Minghua Deng, Baoluo Sun, Chaolong Wang:
Rare variant association tests for ancestry-matched case-control data based on conditional logistic regression. Briefings Bioinform. 23(2) (2022) - [j41]Musu Yuan, Liang Chen, Minghua Deng:
scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasets. Bioinform. 38(3): 738-745 (2022) - [j40]Hui Wan, Liang Chen, Minghua Deng:
scNAME: neighborhood contrastive clustering with ancillary mask estimation for scRNA-seq data. Bioinform. 38(6): 1575-1583 (2022) - [j39]Hui Wan, Liang Chen, Minghua Deng:
scEMAIL: Universal and Source-free Annotation Method for scRNA-seq Data with Novel Cell-type Perception. Genom. Proteom. Bioinform. 20(5): 939-958 (2022) - [j38]Liang Chen, Hui Wan, Qiuyan He, Shun He, Minghua Deng:
Statistical Methods for Microbiome Compositional Data Network Inference: A Survey. J. Comput. Biol. 29(7): 704-723 (2022) - [j37]Juan Xie, Shiwei Wang, Youjun Xu, Minghua Deng, Luhua Lai:
Uncovering the Dominant Motion Modes of Allosteric Regulation Improves Allosteric Site Prediction. J. Chem. Inf. Model. 62(1): 187-195 (2022) - [j36]Wei Ju, Xiao Luo, Zeyu Ma, Junwei Yang, Minghua Deng, Ming Zhang:
GHNN: Graph Harmonic Neural Networks for semi-supervised graph-level classification. Neural Networks 151: 70-79 (2022) - [j35]Yan Wu, Lingfeng Xue, Wen Huang, Minghua Deng, Yihan Lin:
Profiling transcription factor activity dynamics using intronic reads in time-series transcriptome data. PLoS Comput. Biol. 18(1) (2022) - [j34]Xiao Luo, Zeyu Ma, Wei Cheng, Minghua Deng:
Improve Deep Unsupervised Hashing via Structural and Intrinsic Similarity Learning. IEEE Signal Process. Lett. 29: 602-606 (2022) - [c36]Shengsen Wu, Liang Chen, Yihang Lou, Yan Bai, Tao Bai, Minghua Deng, Ling-Yu Duan:
Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation. AAAI 2022: 2722-2730 - [c35]Liang Chen, Qianjin Du, Yihang Lou, Jianzhong He, Tao Bai, Minghua Deng:
Mutual Nearest Neighbor Contrast and Hybrid Prototype Self-Training for Universal Domain Adaptation. AAAI 2022: 6248-6257 - [c34]Liang Chen, Yihang Lou, Jianzhong He, Tao Bai, Minghua Deng:
Evidential Neighborhood Contrastive Learning for Universal Domain Adaptation. AAAI 2022: 6258-6267 - [c33]Liang Chen, Yihang Lou, Jianzhong He, Tao Bai, Minghua Deng:
Geometric Anchor Correspondence Mining with Uncertainty Modeling for Universal Domain Adaptation. CVPR 2022: 16113-16122 - [c32]Zeyu Ma, Yuhang Guo, Xiao Luo, Chong Chen, Minghua Deng, Wei Cheng, Guangming Lu:
DHWP: Learning High-Quality Short Hash Codes Via Weight Pruning. ICASSP 2022: 4783-4787 - [c31]Xiao Luo, Wei Ju, Meng Qu, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
DualGraph: Improving Semi-supervised Graph Classification via Dual Contrastive Learning. ICDE 2022: 699-712 - [c30]Zeyu Ma, Xiao Luo, Yingjie Chen, Mixiao Hou, Jinxing Li, Minghua Deng, Guangming Lu:
Improved Deep Unsupervised Hashing with Fine-grained Semantic Similarity Mining for Multi-Label Image Retrieval. IJCAI 2022: 1254-1260 - [c29]Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
TGNN: A Joint Semi-supervised Framework for Graph-level Classification. IJCAI 2022: 2122-2128 - 2021
- [j33]Liang Chen, Qiuyan He, Yuyao Zhai, Minghua Deng:
Single-cell RNA-seq data semi-supervised clustering and annotation via structural regularized domain adaptation. Bioinform. 37(6): 775-784 (2021) - [c28]Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua:
Graph Contrastive Clustering. ICCV 2021: 9204-9213 - [c27]Daqing Wu, Xiao Luo, Zeyu Ma, Chong Chen, Pengfei Wang, Minghua Deng, Jinwen Ma:
Composition-Enhanced Graph Collaborative Filtering for Multi-behavior Recommendation. ICDM 2021: 1427-1432 - [c26]Yuhang Guo, Xiao Luo, Liang Chen, Minghua Deng:
DNA-GCN: Graph Convolutional Networks for Predicting DNA-Protein Binding. ICIC (3) 2021: 458-466 - [c25]Xiao Luo, Zeyu Ma, Daqing Wu, Huasong Zhong, Chong Chen, Jinwen Ma, Minghua Deng:
Deep Unsupervised Hashing by Distilled Smooth Guidance. ICME 2021: 1-6 - [c24]Xiao Luo, Daqing Wu, Chong Chen, Jinwen Ma, Minghua Deng:
Deep Unsupervised Hashing by Global and Local Consistency. ICME 2021: 1-6 - [c23]Xiao Luo, Yuhang Guo, Zeyu Ma, Huasong Zhong, Tao Li, Wei Ju, Chong Chen, Minghua Deng:
Deep Supervised Hashing by Classification for Image Retrieval. ICONIP (4) 2021: 3-14 - [c22]Daqing Wu, Xiao Luo, Xiangyang Guo, Chong Chen, Minghua Deng, Jinwen Ma:
Concordant Contrastive Learning for Semi-supervised Node Classification on Graph. ICONIP (1) 2021: 584-595 - [c21]Weinan Wang, Yuhang Guo, Wei Ju, Xiao Luo, Minghua Deng:
An Interpretation of Convolutional Neural Networks for Motif Finding from the View of Probability. ICTAI 2021: 176-183 - [c20]Xiao Luo, Daqing Wu, Zeyu Ma, Chong Chen, Minghua Deng, Jinwen Ma, Zhongming Jin, Jianqiang Huang, Xian-Sheng Hua:
CIMON: Towards High-quality Hash Codes. IJCAI 2021: 902-908 - [c19]Daqing Wu, Xiao Luo, Zeyu Ma, Chong Chen, Minghua Deng, Jinwen Ma:
ARGO: Modeling Heterogeneity in E-commerce Recommendation. IJCNN 2021: 1-8 - [c18]Xiao Luo, Daqing Wu, Zeyu Ma, Chong Chen, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua:
A Statistical Approach to Mining Semantic Similarity for Deep Unsupervised Hashing. ACM Multimedia 2021: 4306-4314 - [i9]Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua:
Graph Contrastive Clustering. CoRR abs/2104.01429 (2021) - [i8]Xiao Luo, Zeyu Ma, Daqing Wu, Huasong Zhong, Chong Chen, Jinwen Ma, Minghua Deng:
Deep Unsupervised Hashing by Distilled Smooth Guidance. CoRR abs/2105.06125 (2021) - [i7]Xiao Luo, Daqing Wu, Chong Chen, Jinwen Ma, Minghua Deng, Chen Shen, Jianqiang Huang, Xian-Sheng Hua:
Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation. CoRR abs/2105.11876 (2021) - [i6]Yuhang Guo, Xiao Luo, Liang Chen, Minghua Deng:
DNA-GCN: Graph convolutional networks for predicting DNA-protein binding. CoRR abs/2106.01836 (2021) - [i5]Shengsen Wu, Liang Chen, Yihang Lou, Yan Bai, Tao Bai, Minghua Deng, Lingyu Duan:
Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation. CoRR abs/2108.03372 (2021) - [i4]Daqing Wu, Xiao Luo, Zeyu Ma, Chong Chen, Minghua Deng, Jinwen Ma:
ARGO: Modeling Heterogeneity in E-commerce Recommendation. CoRR abs/2109.05789 (2021) - 2020
- [j32]Xiao Luo, Xinming Tu, Yang Ding, Ge Gao, Minghua Deng:
Expectation pooling: an effective and interpretable pooling method for predicting DNA-protein binding. Bioinform. 36(5): 1405-1412 (2020) - [j31]Chong Chen, Changjing Wu, Linjie Wu, Xiaochen Wang, Minghua Deng, Ruibin Xi:
scRMD: imputation for single cell RNA-seq data via robust matrix decomposition. Bioinform. 36(10): 3156-3161 (2020) - [j30]Liang Chen, Shun He, Yuyao Zhai, Minghua Deng:
Direct interaction network inference for compositional data via codaloss. J. Bioinform. Comput. Biol. 18(6): 2050037:1-2050037:26 (2020) - [j29]Minghua Deng, Jianfeng Feng, Hong Qian, Lin Wan, Fengzhu Sun:
International Workshop on Applications of Probability and Statistics to Biology, July 11-13, 2019. Quant. Biol. 8(2): 177-186 (2020) - [i3]Xiao Luo, Chong Chen, Huasong Zhong, Hao Zhang, Minghua Deng, Jianqiang Huang, Xiansheng Hua:
A Survey on Deep Hashing Methods. CoRR abs/2003.03369 (2020) - [i2]Xiao Luo, Daqing Wu, Zeyu Ma, Chong Chen, Huasong Zhong, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua:
CIMON: Towards High-quality Hash Codes. CoRR abs/2010.07804 (2020)
2010 – 2019
- 2019
- [j28]Huili Yuan, Shun He, Minghua Deng:
Compositional data network analysis via lasso penalized D-trace loss. Bioinform. 35(18): 3404-3411 (2019) - [j27]Haicang Zhang, Qi Zhang, Fusong Ju, Jianwei Zhu, Yujuan Gao, Ziwei Xie, Minghua Deng, Shiwei Sun, Wei-Mou Zheng, Dongbo Bu:
Predicting protein inter-residue contacts using composite likelihood maximization and deep learning. BMC Bioinform. 20(1): 537:1-537:11 (2019) - [j26]Haicang Zhang, Qi Zhang, Fusong Ju, Jianwei Zhu, Yujuan Gao, Ziwei Xie, Minghua Deng, Shiwei Sun, Wei-Mou Zheng, Dongbo Bu:
Correction to: Predicting protein inter-residue contacts using composite likelihood maximization and deep learning. BMC Bioinform. 20(1): 616:1-616:5 (2019) - [j25]Yishu Wang, Huaying Fang, Dejie Yang, Hongyu Zhao, Minghua Deng:
Network Clustering Analysis Using Mixture Exponential-Family Random Graph Models and Its Application in Genetic Interaction Data. IEEE ACM Trans. Comput. Biol. Bioinform. 16(5): 1743-1752 (2019) - 2018
- [j24]Yujuan Gao, Sheng Wang, Minghua Deng, Jinbo Xu:
RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning. BMC Bioinform. 19-S(4): 73-84 (2018) - [i1]Haicang Zhang, Qi Zhang, Fusong Ju, Jianwei Zhu, Shiwei Sun, Yujuan Gao, Ziwei Xie, Minghua Deng, Shiwei Sun, Wei-Mou Zheng, Dongbo Bu:
Predicting protein inter-residue contacts using composite likelihood maximization and deep learning. CoRR abs/1809.00083 (2018) - 2017
- [j23]Zengmiao Wang, Huaying Fang, Nelson L. S. Tang, Minghua Deng:
VCNet: vector-based gene co-expression network construction and its application to RNA-seq data. Bioinform. 33(14): 2173-2181 (2017) - [j22]Yuchao Xia, Yun Liu, Minghua Deng, Ruibin Xi:
SVmine improves structural variation detection by integrative mining of predictions from multiple algorithms. Bioinform. 33(21): 3348-3354 (2017) - [j21]Yuchao Xia, Yun Liu, Minghua Deng, Ruibin Xi:
Pysim-sv: a package for simulating structural variation data with GC-biases. BMC Bioinform. 18(S-3): 23-30 (2017) - [j20]Huaying Fang, Chengcheng Huang, Hongyu Zhao, Minghua Deng:
gCoda: Conditional Dependence Network Inference for Compositional Data. J. Comput. Biol. 24(7): 699-708 (2017) - 2016
- [j19]Jie Ren, Kai Song, Minghua Deng, Gesine Reinert, Charles H. Cannon, Fengzhu Sun:
Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics. Bioinform. 32(7): 993-1000 (2016) - [j18]Huili Yuan, Zhenye Li, Nelson L. S. Tang, Minghua Deng:
A network based covariance test for detecting multivariate eQTL in saccharomyces cerevisiae. BMC Syst. Biol. 10(S-1): 8 (2016) - 2015
- [j17]Huaying Fang, Chengcheng Huang, Hongyu Zhao, Minghua Deng:
CCLasso: correlation inference for compositional data through Lasso. Bioinform. 31(19): 3172-3180 (2015) - [j16]Zengmiao Wang, Jun Wang, Changjing Wu, Minghua Deng:
Estimation of isoform expression in RNA-seq data using a hierarchical Bayesian model. J. Bioinform. Comput. Biol. 13(6): 1542001:1-1542001:15 (2015) - 2014
- [j15]Kai Song, Jie Ren, Gesine Reinert, Minghua Deng, Michael S. Waterman, Fengzhu Sun:
New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing. Briefings Bioinform. 15(3): 343-353 (2014) - 2013
- [j14]Jie Ren, Kai Song, Fengzhu Sun, Minghua Deng, Gesine Reinert:
Multiple alignment-free sequence comparison. Bioinform. 29(21): 2690-2698 (2013) - [j13]Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng, Fengzhu Sun:
Alignment-Free Sequence Comparison Based on Next-Generation Sequencing Reads. J. Comput. Biol. 20(2): 64-79 (2013) - [e1]Minghua Deng, Rui Jiang, Fengzhu Sun, Xuegong Zhang:
Research in Computational Molecular Biology - 17th Annual International Conference, RECOMB 2013, Beijing, China, April 7-10, 2013. Proceedings. Lecture Notes in Computer Science 7821, Springer 2013, ISBN 978-3-642-37194-3 [contents] - 2012
- [c17]Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng, Fengzhu Sun:
Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads: Extended Abstract. RECOMB 2012: 272-285 - 2011
- [j12]Lin Hou, Lin Wang, Minping Qian, Dong Li, Chao Tang, Yunping Zhu, Minghua Deng, Fangting Li:
Modular analysis of the probabilistic genetic interaction network. Bioinform. 27(6): 853-859 (2011) - [j11]Yiming Lu, Yang Zhou, Wubin Qu, Minghua Deng, Chenggang Zhang:
A Lasso regression model for the construction of microRNA-target regulatory networks. Bioinform. 27(17): 2406-2413 (2011) - [j10]Lin Wang, Lin Hou, Minping Qian, Fangting Li, Minghua Deng:
Integrating multiple types of data to predict novel cell cycle-related genes. BMC Syst. Biol. 5(S-1): S9 (2011) - [p1]Hyonho Chun, Jia Kang, Xianghua Zhang, Minghua Deng, Haisu Ma, Hongyu Zhao:
Reverse Engineering of Gene Regulation Networks with an Application to the DREAM4 in silico Network Challenge. Handbook of Statistical Bioinformatics 2011: 461-477 - 2010
- [j9]Naifang Su, Yufu Wang, Minping Qian, Minghua Deng:
Combinatorial regulation of transcription factors and microRNAs. BMC Syst. Biol. 4: 150 (2010) - [j8]Quan Chen, Minghua Deng, Minping Qian, Lin Wan, Yi Xiao:
The Biases of Copy Numbers from Affymetrix SNP Arrays and Their Corrections. Commun. Inf. Syst. 10(2): 83-98 (2010) - [j7]Dengguo Wei, Hao Zheng, Naifang Su, Minghua Deng, Luhua Lai:
Binding Energy Landscape Analysis Helps to Discriminate True Hits from High-Scoring Decoys in Virtual Screening. J. Chem. Inf. Model. 50(10): 1855-1864 (2010) - [c16]Quan Wang, Linbo Wang, Minping Qian, Minghua Deng:
A hybridization model for tiling array analysis. BIBM Workshops 2010: 148-151
2000 – 2009
- 2009
- [j6]Quan Wang, Lin Wan, Dayong Li, Lihuang Zhu, Minping Qian, Minghua Deng:
Searching for bidirectional promoters in Arabidopsis thaliana. BMC Bioinform. 10(S-1) (2009) - [j5]Hao Zheng, Xingyi Hang, Ji Zhu, Minping Qian, Wubin Qu, Chenggang Zhang, Minghua Deng:
REMAS: a new regression model to identify alternative splicing events from exon array data. BMC Bioinform. 10(S-1) (2009) - [c15]Fugui Wang, Lin Hou, Jiangfeng Xu, Minping Qian, Minghua Deng:
A Robust Empirical Bayesian Method for Detecting Differentially Expressed Genes. BMEI 2009: 1-5 - [c14]Wei Wei, Lin Wan, Minping Qian, Minghua Deng:
The Implementation and Application of the Microarray Preprocessing Generalized PDNN Model. BMEI 2009: 1-5 - [c13]Hao Zheng, Fugui Wang, Jiangfeng Xu, Nengfeng Zhou, Minping Qian, Ji Zhu, Minghua Deng:
Pathway Detection Based on Hierarchical LASSO Regression Model. BMEI 2009: 1-7 - [c12]Jingwei Liu, Minghua Deng, Minping Qian:
Feature-Based Causal Structure Discovery in Protein and Gene Expression Data with Bayesian Network. ICNC (2) 2009: 144-148 - 2008
- [c11]Lin Wan, Wenjiang J. Fu, Minghua Deng, Minping Qian:
A Method to Correct Systematic Bias in Affymetrix SNP Arrays. BMEI (1) 2008: 442-446 - [c10]Wenjiang J. Fu, Ming Li, Lin Wan, Minghua Deng, Minping Qian:
On Design of Oligonucleotide SNP Arrays and Methods for Genotype Calling. BMEI (1) 2008: 453-458 - 2006
- [j4]Hyunju Lee, Minghua Deng, Fengzhu Sun, Ting Chen:
An integrated approach to the prediction of domain-domain interactions. BMC Bioinform. 7: 269 (2006) - [c9]Huan Yu, Minping Qian, Minghua Deng:
Using a Stochastic AdaBoost Algorithm to Discover Interactome Motif Pairs from Sequences. ICIC (3) 2006: 622-630 - [c8]Yuping Zhang, Huan Yu, Minghua Deng, Minping Qian:
Nonequilibrium Model for Yeast Cell Cycle. ICIC (3) 2006: 786-791 - 2004
- [j3]Minghua Deng, Zhidong Tu, Fengzhu Sun, Ting Chen:
Mapping gene ontology to proteins based on protein-protein interaction data. Bioinform. 20(6): 895-902 (2004) - [j2]Minghua Deng, Ting Chen, Fengzhu Sun:
An Integrated Probabilistic Model for Functional Prediction of Proteins. J. Comput. Biol. 11(2/3): 463-475 (2004) - [c7]Gert R. G. Lanckriet, Minghua Deng, Nello Cristianini, Michael I. Jordan, William Stafford Noble:
Kernel-Based Data Fusion and Its Application to Protein Function Prediction in Yeast. Pacific Symposium on Biocomputing 2004: 300-311 - [c6]Shenglan Peng, Minghua Deng, Minping Qian:
An Improvement for Eulerian Path of Assembly. SNPD 2004: 97-105 - 2003
- [j1]Minghua Deng, Kui Zhang, Shipra Mehta, Ting Chen, Fengzhu Sun:
Prediction of Protein Function Using Protein-Protein Interaction Data. J. Comput. Biol. 10(6): 947-960 (2003) - [c5]Minghua Deng, Fengzhu Sun, Ting Chen:
Assessment of the reliability of protein-protein interactions and protein function prediction. Pacific Symposium on Biocomputing 2003: 140-151 - [c4]Minghua Deng, Ting Chen, Fengzhu Sun:
An integrated probabilistic model for functional prediction of proteins. RECOMB 2003: 95-103 - 2002
- [c3]Minghua Deng, Kui Zhang, Shipra Mehta, Ting Chen, Fengzhu Sun:
Prediction of Protein Function Using Protein-Protein Interaction Data. CSB 2002: 197-206 - [c2]Minghua Deng, Shipra Mehta, Fengzhu Sun, Ting Chen:
Inferring domain-domain interactions from protein-protein interactions. RECOMB 2002: 117-126 - 2000
- [c1]Feng Qi, Minghua Deng, Minping Qian, Xueqing Zhu:
A Novel Algorithm for Handwritten Chinese Character Recognition. ICMI 2000: 379-385
Coauthor Index
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