Author

Yitao Zhou

Xiamen UniversityORCID 0009-0004-9413-8218Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Yitao Zhou1 paper · Fujian Normal University

Biology Disciplines

Click to filter author papers

Bioinformatics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 2 Assay:scRNA-seq· 2 Approach:variational autoencoder· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:contrastive learning· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1

Frequent Co-Authors

Fan YangiD· 2 shared Feng ZengiD· 2 shared Han LiiD· 1 shared Ningyuan ZhaoiD· 1 shared Ying WangiD· 1 shared Yongxuan LaiiD· 1 shared

Activity by Year

2023-2024 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Fan YangORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsComputers in Biology and MedicinePeer-reviewedApr 16, 2024

ISMI-VAE: A Deep Learning Model for Classifying Disease Cells Using Gene Expression and SNV Data

Han Li, Yitao Zhou, Ningyuan Zhao…·Fan Yang

This paper introduces ISMI-VAE, a deep learning model that integrates SNV and gene expression data to classify disease cells, showing improved effectiveness and interpretability.

6 citations

𝕏 PostBluesky

BioinformaticsbioRxivPreprintDec 22, 2023

OmniClustifyXMBD: Uncover putative cell stateswithin multiple single-cell omics datasets

Fan Yang, Yitao Zhou, Feng Zeng

OmniClustifyXMBD identifies putative cell states across diverse single-cell omics datasets by integrating adaptive signal isolation with a deep variational Gaussian mixture model clustering algorithm.

DOI 10.1101/2023.12.22.573159

scRNA-seqdeep learning

𝕏 PostBluesky