Author

Xuwen Kong

Xiamen University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:differential expression· 2 Organism:human· 2 Assay:scRNA-seq· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Feng ZengiD· 2 shared Jiahuai HaniD· 2 shared Ting CheniD· 2 shared Fan YangiD· 1 shared Fan YangiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 9 mutual co-author links

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2 shared papersBioinformatics

Feng ZengORCID

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2 papers

Recent·Most cited

Extraction of biological signals by factorization enables the reliable analysis of single-cell transcriptomics

Feng Zeng, Xuwen Kong, Fan Yang, Ting Chen, Jiahuai Han

This paper introduces scPhenoXMBD, a deep auto-regressive factor model that extracts biological signals from single-cell transcriptomics data, improving analysis reliability and enabling better identification of IFNβ-responsive pathways.

bioRxiv · Mar 4, 2023 · PreprintBioinformatics

scPheno: A deep generative model to integrate scRNA-seq with disease phenotypes and its application on prediction of COVID-19 pneumonia and severe assessment

Feng Zeng, Xuwen Kong, Fan Yang, Ting Chen, Jiahuai Han

scPheno integrates scRNA-seq with disease phenotypes to identify transcriptional variations linked to COVID-19 diagnosis and severity, achieving 81.3% accuracy using 4 genes.

bioRxiv · Jun 20, 2022 · PreprintGenomics