Author

Jung Min Han

National Institute of Arthritis and Musculoskeletal and Skin DiseasesORCID 0000-0002-2253-4156Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genomics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:batch correction / integration· 1 Organism:Drosophila· 1 Research Focus:gene regulatory network inference· 1 Organism:mouse· 1

Frequent Co-Authors

Heidi H. KongiD· 1 shared Isaac BrownelliD· 1 shared Jay‐Hyun JoiD· 1 shared Lingling MiaoiD· 1 shared Loren ColladoiD· 1 shared Michael C. KellyiD· 1 shared Savannah BarkdulliD· 1 shared Stefania Dell’OrsoiD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperGenomics

Heidi H. KongORCID

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2 papers

Recent·Most cited

GenomicsbioRxivPreprintOct 21, 2024

Estimating and correcting index hopping misassignments in single-cell RNA-seq data

Lingling Miao, Loren Collado, Savannah Barkdull…·Isaac Brownell

The paper estimates and corrects index hopping misassignments in scRNA-seq data by analyzing signature genes across cell types and adjusting expression levels.

DOI 10.1101/2024.10.21.619353

mousescRNA-seq

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Systems BiologybioRxivPreprintMay 12, 2021

Mechanistic Gene Networks Inferred from Single-Cell Data are Better Predictors than Neural Networks.

Jung Min Han, Sudheesha Perera, Zeba Wunderlich, Vipul Periwal

The paper infers mechanistic gene networks from single-cell data and shows they outperform neural networks in predicting gene dynamics and knockout effects.

DOI 10.1101/2021.05.12.443819

DrosophilascRNA-seq

𝕏 PostBluesky