Author

Sarbottam Piya

Biogen (United States)ORCID 0000-0002-1070-8008Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Assay:spatial transcriptomics· 3 Approach:statistical model· 3 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Organism:human· 1 Organism:mouse· 1

Frequent Co-Authors

Baohong ZhangiD· 3 shared Wenxing HuiD· 3 shared Hui‐Hsin TsaiiD· 2 shared Jake Gagnon· 2 shared Matthew M. Ryals· 2 shared Patrick F. Cullen· 2 shared Shaolong CaoiD· 2 shared Su Jing ChaniD· 2 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersNeuroscience

Baohong ZhangORCID

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3 papers

Recent·Most cited

NeuroscienceFrontiers in BioinformaticsPeer-reviewedAug 6, 2026

Spatial transcriptomics reveals heterogeneous cell-cell interactions among brain regions in a cuprizone model consistent with multiple sclerosis lesions

Hui‐Hsin Tsai, Sarbottam Piya, Jing Wang…·Baohong Zhang

The paper uses spatial transcriptomics to analyze cell-cell interactions in a cuprizone model, finding region-specific changes and partial translatability to multiple sclerosis lesions.

DOI 10.3389/fbinf.2026.1832826

mousespatial transcriptomics

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BioinformaticsJournal of Advance Research in Pharmacy & Biological SciencePeer-reviewedJan 19, 2026

SpaceSequest: A unified pipeline for spatial transcriptomics data analysis

Yu Henry Sun, Sarbottam Piya, Zhengyu Ouyang…·Baohong Zhang

SpaceSequest provides a unified pipeline for analyzing spatial transcriptomics data from multiple platforms, enabling standardized processing, analysis, and visualization.

2 citations

spatial transcriptomicsstatistical model

𝕏 PostBluesky

GenomicsNature MethodsPeer-reviewedSep 1, 2025

Scaling up spatial transcriptomics for large-sized tissues: uncovering cellular-level tissue architecture beyond conventional platforms with iSCALE

Amelia R. Schroeder, Melanie Loth, Chunyu Luo…·Mingyao Li

iSCALE predicts super-resolution gene expression and annotates tissue architecture in large tissues, revealing features missed by conventional spatial transcriptomics.

31 citationstop 1%

humanspatial transcriptomics

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