Author

Seowon Chang

Brown 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:batch correction / integration· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:imaging· 1 Assay:metabolomics· 1 Assay:proteomics· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Ying MaiD· 2 shared Alexander FleischmanniD· 1 shared Björn SandstedeiD· 1 shared Ritambhara SinghiD· 1 shared Wenjun ZhaoiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

5 top collaborators · 7 mutual co-author links

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2 shared papersBioinformatics

Ying MaORCID

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2 papers

Recent·Most cited

Scalable, Generalizable, and Uncertainty-Aware Integration of Spatial Multi-Omics Across Diverse Modalities and Platforms with SCIGMA

Seowon Chang, Alexander Fleischmann, Ying Ma

SCIGMA integrates spatial multi-omics data across modalities and platforms using a deep learning framework with uncertainty-aware contrastive learning, outperforming existing methods in domain detection and modality preservation.

Nature Genetics · Sep 1, 2026Peer-reviewedBioinformatics

Cell type-specific gene regulatory network inference from single cell transcriptomics with ctOTVelo

Seowon Chang, Wenjun Zhao, Ying Ma, Björn Sandstede, Ritambhara Singh

The paper introduces ctOTVelo, a method for inferring cell type-specific gene regulatory networks from single-cell transcriptomics data, achieving state-of-the-art performance.

bioRxiv · Mar 14, 2026 · PreprintGenomics