Author

D. Barwinska

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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Cell Biology· 1 Pathology· 1 Physiology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Organism:human· 3 Approach:deep learning· 2 Assay:imaging· 2 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

S. Khochare· 3 shared S. Winfree· 3 shared T. M. El-Achkar· 3 shared J. E. Lingeman· 2 shared K. J. Kelly· 2 shared K. W. Dunn· 2 shared M. T. Eadon· 2 shared A. F. Almulhim· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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3 shared papersPhysiology

S. Khochare

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Author profile →

3 papers

Recent·Most cited

Integrated cytometry with machine learning applied to high-content imaging of human kidney tissue for in-situ cell classification and neighborhood analysis

S. Winfree, A. T. McNutt, S. Khochare, T. J. Borgard, D. Barwinska, A. R. Sabo, M. J. Ferkowicz, J. C. Williams, J. E. Lingeman, C. J. Gulbronson, K. J. Kelly, T. A. Sutton, P. C. Dagher, M. T. Eadon, K. W. Dunn, T. M. El-Achkar

The paper introduces VTEA, a software tool that integrates machine learning and cytometry analysis for high-content imaging of human kidney tissue to classify cells and analyze their spatial neighborhoods.

bioRxiv · Dec 27, 2021Physiology

In situ classification of cell types in human kidney tissue using 3D nuclear staining

A. Woloshuk, S. Khochare, A. F. Almulhim, A. McNutt, D. Dean, D. Barwinska, M. Ferkowicz, M. T. Eadon, K. J. Kelly, K. W. Dunn, M. A. Hasan, T. M. El-Achkar, S. Winfree

This paper develops a deep learning method using 3D nuclear staining to classify cell types in human kidney tissue without requiring specific markers.

bioRxiv · Jun 24, 2020Cell Biology

A precision medicine approach uncovers a unique signature of neutrophils in patients with brushite kidney stones

M. S. Makki, S. Winfree, J. E. Lingeman, F. A. Witzmann, E. M. Worcester, A. Krambeck, F. Coe, A. P. Evan, S. Bledsoe, K. Bergsland, S. Khochare, D. Barwinska, J. C. Willliams, T. M. El-Achkar

This study identifies a unique neutrophil signature in brushite kidney stone formers through multi-omics analysis, linking increased neutrophil infiltration and NETosis to tissue scarring and inflammation.

bioRxiv · Nov 16, 2019Pathology