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Minghua Deng

Showing results (1-10 of 137) with videos related to

Pageof 14
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Plos One|July 25, 2019
Direct interaction network and differential network inference from compositional data via lasso penalized D-trace lossShun He, Minghua Deng
Genes|May 15, 2020
Sparsity-Penalized Stacked Denoising Autoencoders for Imputing Single-Cell RNA-Seq DataWeilai Chi, Minghua Deng
Biomed Research International|August 15, 2015
Low-Rank and Sparse Matrix Decomposition for Genetic Interaction DataYishu Wang, Dejie Yang, Minghua Deng
Bioinformatics (Oxford, England)|October 8, 2021
scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasetsMusu Yuan, Liang Chen, Minghua Deng
Frontiers in Genetics|September 8, 2022
Clustering CITE-seq data with a canonical correlation-based deep learning methodMusu Yuan, Liang Chen, Minghua Deng
Briefings in Bioinformatics|March 4, 2023
scGAD: a new task and end-to-end framework for generalized cell type annotation and discoveryYuyao Zhai, Liang Chen, Minghua Deng
BMC Bioinformatics|August 4, 2025
Semi-supervised contrastive learning variational autoencoder Integrating single-cell multimodal mosaic datasetsZihao Wang, Zeyu Wu, Minghua Deng
Briefings in Bioinformatics|February 17, 2024
scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq dataYuyao Zhai, Liang Chen, Minghua Deng
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|August 3, 2004
An integrated probabilistic model for functional prediction of proteinsMinghua Deng, Ting Chen, Fengzhu Sun
Bioinformatics (Oxford, England)|January 9, 2022
scNAME: neighborhood contrastive clustering with ancillary mask estimation for scRNA-seq dataHui Wan, Liang Chen, Minghua Deng
Pageof 14

Showing results (1-10 of 137) with videos related to

Sort By:
Pageof 14
Plos One|July 25, 2019
Direct interaction network and differential network inference from compositional data via lasso penalized D-trace lossShun He, Minghua Deng
Genes|May 15, 2020
Sparsity-Penalized Stacked Denoising Autoencoders for Imputing Single-Cell RNA-Seq DataWeilai Chi, Minghua Deng
Biomed Research International|August 15, 2015
Low-Rank and Sparse Matrix Decomposition for Genetic Interaction DataYishu Wang, Dejie Yang, Minghua Deng
Bioinformatics (Oxford, England)|October 8, 2021
scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasetsMusu Yuan, Liang Chen, Minghua Deng
Frontiers in Genetics|September 8, 2022
Clustering CITE-seq data with a canonical correlation-based deep learning methodMusu Yuan, Liang Chen, Minghua Deng
Briefings in Bioinformatics|March 4, 2023
scGAD: a new task and end-to-end framework for generalized cell type annotation and discoveryYuyao Zhai, Liang Chen, Minghua Deng
BMC Bioinformatics|August 4, 2025
Semi-supervised contrastive learning variational autoencoder Integrating single-cell multimodal mosaic datasetsZihao Wang, Zeyu Wu, Minghua Deng
Briefings in Bioinformatics|February 17, 2024
scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq dataYuyao Zhai, Liang Chen, Minghua Deng
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|August 3, 2004
An integrated probabilistic model for functional prediction of proteinsMinghua Deng, Ting Chen, Fengzhu Sun
Bioinformatics (Oxford, England)|January 9, 2022
scNAME: neighborhood contrastive clustering with ancillary mask estimation for scRNA-seq dataHui Wan, Liang Chen, Minghua Deng
Pageof 14