Author

Hui Li

Sichuan Agricultural UniversityORCID 0000-0002-0406-9203Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Hui Li16 papers · Shanghai Jiao Tong University

Biology Disciplines

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Bioinformatics· 2 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:batch correction / integration· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Cory BrouweriD· 1 shared Davis James McCarthyiD· 1 shared Heejung ShimiD· 1 shared Junjie ZhangiD· 1 shared Li LuoiD· 1 shared Susan H. WeiiD· 1 shared Weijun LuoiD· 1 shared Yangping LiiD· 1 shared

Activity by Year

2022-2022 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperBioinformatics

Cory BrouwerORCID

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3 papers

Recent·Most cited

BioinformaticsBMC BioinformaticsPeer-reviewedNov 3, 2022

Trade-off between conservation of biological variation and batch effect removal in deep generative modeling for single-cell transcriptomics

Hui Li, Davis James McCarthy, Heejung Shim, Susan H. Wei

This paper explores the trade-off between preserving biological variation and removing batch effects in scRNA-seq data using Pareto multi-task learning and Mutual Information Neural Estimation.

10 citations

scRNA-seqdeep learning

Molecular BiologybioRxivPreprintJul 31, 2022

ZmWRKY82-ZmSLG regulate seed development by modulating brassionsteroid homeostasis in maize

Hui Li, Yayun Wang, Li Luo…·Yubi Huang

The paper identifies ZmWRKY82 and ZmSLG1 as regulators of brassinosteroid homeostasis in maize seeds, showing their role in seed development and yield potential.

DOI 10.1101/2022.07.31.502243

zebrafishbulk RNA-seq

BioinformaticsNature CommunicationsPeer-reviewedApr 7, 2022

A Universal Deep Neural Network for In-Depth Cleaning of Single-Cell RNA-Seq Data

Hui Li, Cory Brouwer, Weijun Luo

AutoClass is a deep neural network for cleaning scRNA-Seq data, outperforming existing methods in noise removal and analysis tasks.

58 citationstop 4%

scRNA-seqdeep learning