Author

Xu Su

UConn HealthORCID 0009-0003-3000-271XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:spatial domain detection· 2 Assay:spatial transcriptomics· 2 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Dongyuan SongiD· 2 shared Yuxin YiniD· 2 shared Aarya DalaliD· 1 shared Dong CheniD· 1 shared Jiarui JiniD· 1 shared Jinyuan CheniD· 1 shared Lingzhen MengiD· 1 shared Marcial EscuderoiD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersBioinformatics

Dongyuan SongORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 28, 2026

Trustworthy super-resolution reconstruction across spatial omics modalities

Menghan Li, Xutao Wang, Xu Su…·Dongyuan Song

This paper introduces spEnhance, a computational framework that improves spatial resolution and reliability of spot-level spatial omics data across multiple modalities.

DOI 10.64898/2026.09.25.754471

humanspatial transcriptomics

GenomicsbioRxivPreprintSep 17, 2026

Multi-Omics analysis provides crucial insights into ecological adaptation to dryland of a dominant grass (Psammochloa villosa, Poaceae) in Northwest China

Tao Liu, Yuping Liu, Xu Su…·Marcial Escudero

This study uses multi-omics analysis to investigate the genomic basis of ecological adaptation to dryland environments in Psammochloa villosa.

DOI 10.64898/2026.09.14.751419

plant (other)whole-genome sequencing

BioinformaticsbioRxivPreprintSep 12, 2026

spAlignDE unifies cross-sample and cross-modal spatial alignment with mismatch-aware differential expression

Xu Su, Wang Yu, Lingzhen Meng…·Dongyuan Song

spAlignDE aligns spatial omics data across samples and modalities, improving differential expression analysis by accounting for alignment errors and cell-type composition.

DOI 10.64898/2026.09.05.749632

mousespatial transcriptomics