Author

Peng Yin

Harvard UniversityORCID 0000-0002-4773-359XUnclaimed ORCID profile · follow to get notified of new preprints

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Peng Yin4 papers · Harvard University

Biology Disciplines

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Bioinformatics· 1 Cell Biology· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:experimental assay· 2 Organism:mouse· 2 Research Focus:spatial domain detection· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Assay:DNA methylation· 1 Assay:fluorescence / live-cell microscopy· 1

Frequent Co-Authors

Chao-ting WuiD· 3 shared Brian J. BeliveauiD· 2 shared Guy NiriD· 2 shared Hiroshi M. SasakiiD· 2 shared Jocelyn Y. KishiiD· 2 shared S. Dean LeeiD· 2 shared Son C. NguyeniD· 2 shared Ana PomboiD· 1 shared

Activity by Year

2018-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersCell Biology

Chao-ting WuORCID

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3 papers

Recent·Most cited

Cell BiologyProceedings of the National Academy of SciencesPeer-reviewedAug 7, 2025

Cryosectioning-enhanced super-resolution microscopy for single-protein imaging across cells and tissues

Johannes Stein, Maria Ericsson, Michel Nofal…·Chao-ting Wu

The paper introduces tkPAINT, a method combining TIRF microscopy and Tokuyasu cryosectioning to enhance DNA-PAINT for single-protein imaging and molecular counting with 3 nm precision across cells and tissues.

8 citations

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GeneticsPLoS GeneticsPeer-reviewedDec 26, 2018

Walking along chromosomes with super-resolution imaging, contact maps, and integrative modeling

Guy Nir, Irene Farabella, Cynthia Pérez Estrada…·Chao-ting Wu

The paper uses super-resolution imaging and integrative modeling to achieve 10 kb resolution of chromosome folding.

261 citationstop 1%

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BioinformaticsProceedings of the National Academy of SciencesPeer-reviewedFeb 20, 2018

OligoMiner: A rapid, flexible environment for the design of genome-scale oligonucleotide in situ hybridization probes

Brian J. Beliveau, Jocelyn Y. Kishi, Guy Nir…·Peng Yin

OligoMiner designs genome-scale oligo FISH probes with customizable parameters and evaluates probe specificity using supervised learning, demonstrating scalability across model organisms.

257 citationstop 1%

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