Author

Nikolay Samusik

Stanford MedicineORCID 0000-0002-3559-1010Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 3 Research Focus:cell type annotation· 2 Research Focus:cell-cell communication· 2 Research Focus:clustering· 2 Assay:imaging· 2 Research Focus:spatial domain detection· 2 Approach:statistical model· 2 Research Focus:batch correction / integration· 1

Frequent Co-Authors

Garry P. NolaniD· 4 shared Andrew J. GentlesiD· 1 shared Christina S. KongiD· 1 shared Dangna Li· 1 shared Edgar G. EnglemaniD· 1 shared Gustavo VazqueziD· 1 shared Irene LiiD· 1 shared John B. SunwooiD· 1 shared

Activity by Year

2017-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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4 shared papersBioinformatics

Garry P. NolanORCID

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Author profile →

4 papers

Recent·Most cited

Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA reveals novel spatial biology

Weiruo Zhang, Irene Li, Nathan Edward Reticker-Flynn, Zinaida Good, Serena Chang, Nikolay Samusik, Saumyaa Saumyaa, Yuanyuan Li, Xin Zhou, Rachel Liang, Christina S. Kong, Quynh‐Thu Le, Andrew J. Gentles, John B. Sunwoo, Garry P. Nolan, , Sylvia K. Plevritis

CELESTA identifies cell types in multiplexed in situ images by integrating protein expression and spatial information, revealing novel spatial biology associated with lymph node metastasis.

bioRxiv · Feb 2, 2022 · PreprintBioinformatics

Deep profiling of mouse splenic architecture with CODEX multiplexed imaging.

Yury Goltsev, Nikolay Samusik, Julia Kennedy‐Darling, Salil S. Bhate, Matthew B. Hale, Gustavo Vazquez, Sarah Black, Garry P. Nolan

The paper uses CODEX multiplexed imaging to analyze mouse spleen architecture, revealing how cellular neighborhoods affect immune cell receptor expression and identifying altered cell interactions in lupus.

Cell · Aug 1, 2018Peer-reviewedSystems Biology

Continuous visualization of differences between biological conditions in single-cell data

Tyler J. Burns, Garry P. Nolan, Nikolay Samusik

The paper introduces a tool for visualizing differences between biological conditions in single-cell data using overlapping KNN groupings, improving upon traditional partition-based methods.

bioRxiv · Jun 2, 2018 · PreprintSystems Biology

Scalable Multi-Sample Single-Cell Data Analysis by Partition-Assisted Clustering and Multiple Alignments of Networks

Ye Henry Li, Dangna Li, Nikolay Samusik, Xiaowei Wang, Leying Guan, Garry P. Nolan, Wing Hung Wong

PAC-MAN enables scalable analysis of multi-sample CyTOF data by clustering and aligning subpopulations across samples to identify dataset-level cellular states.

PLoS Computational Biology · Dec 27, 2017Peer-reviewedBioinformatics