Author

J. Walston

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioengineering· 3 Ecology· 1 Pathology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 4 Assay:imaging· 4 Organism:human· 3 Research Focus:clustering· 2 Approach:deep learning· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Research Focus:ecology & biodiversity· 1

Frequent Co-Authors

J. M. Phillip· 4 shared B. Starich· 3 shared P.-H. Wu· 3 shared A. Agrawal· 2 shared C. Min· 2 shared D. Wirtz· 2 shared H. Jayatilaka· 2 shared N. Zamponi· 2 shared

Activity by Year

2020-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

4 shared papersBioengineering

J. M. Phillip

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

Single-cell morphology encodes functional subtypes of senescence in aging human dermal fibroblasts

P. Kamat, N. Macaluso, C. Min, Y. Li, A. Agrawal, A. Winston, L. Pan, B. Starich, T. Stewert, P.-H. Wu, J. Fan, J. Walston, J. M. Phillip

This study identifies functional senescence subtypes in aging human dermal fibroblasts using single-cell morphology and machine learning, showing subtype-specific responses to senotherapies.

bioRxiv · May 10, 2024Bioengineering

qMAP Enabled Microanatomical Mapping of Human Skin Aging

K. S. Han, I. B. Sander, J. Kumer, E. P. Resnick, C. Booth, Y. Im, G. Cheng, B. Starich, A. L. Kiemen, J. M. Phillip, S. Reddy, C. Joshu, J. Sunshine, J. Walston, D. Wirtz, P.-H. Wu

This study introduces qMAP, a deep learning-based workflow for microanatomical mapping of human skin, identifying 10 core processes strongly associated with aging and achieving age prediction accuracy comparable to epigenetic clocks.

bioRxiv · Apr 3, 2024 · PreprintPathology

Profiling Dynamic Patterns of Single-cell Motility

D. Maity, N. Sivakumar, P. Kamat, N. Zamponi, C. Min, W. Du, H. Jayatilaka, A. Giri, A. Johnston, B. Starich, M. Karl, A. Agrawal, D. Riley, L. Venturitti, A. Melnick, , J. M. Phillip

This study introduces CaMI, a framework to classify single-cell motility patterns, revealing heterogeneity and dynamics not captured by traditional ensemble methods.

bioRxiv · Sep 21, 2022Bioengineering

Fractional re-distribution among cell motility states during ageing

J. M. Phillip, N. Zamponi, M. P. Phillip, J. Daya, S. McGovern, W. Williams, K. Tschudi, H. Jayatilaka, P.-H. Wu, J. Walston, D. Wirtz

The paper shows that ageing reduces cell motility heterogeneity by redistributing cells among motility states rather than uniformly decreasing motility.

bioRxiv · Apr 29, 2020Bioengineering

Modification of forests by people means only 40% of remaining forests have high ecosystem integrity

H. S. Grantham, A. Duncan, T. D. Evans, K. R. Jones, H. Beyer, R. Schuster, J. Walston, J. Ray, J. Robinson, M. Callow, T. Clements, H. Costa, A. DeGemmis, P. R. Elsen, J. Ervin, , S. Wang

The paper quantifies global forest modification, finding 40.5% of remaining forests have high ecosystem integrity, mostly in specific regions, and highlights the need for policies to protect these areas.

bioRxiv · Mar 5, 2020 · PreprintEcology