Author

C. T. Combs

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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Biophysics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Organism:human· 1 Assay:imaging· 1 Approach:transformer / foundation model· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

D. D. Seith· 2 shared Z. S. Siwy· 2 shared M. J. Bovyn· 1 shared S. P. Gross· 1 shared X. Xie· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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2 shared papersBiophysics

D. D. Seith

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2 papers

Recent·Most cited

Deformability Cytometry Clustering with Variational Autoencoders

D. D. Seith, C. T. Combs, Z. S. Siwy

This paper uses a variational autoencoder with a clustering loss to perform unsupervised classification of cells based on their mechanical properties.

bioRxiv · Oct 1, 2022 · PreprintBiophysics

Deep Learning Assisted Mechanotyping of Individual Cells Through Repeated Deformations and Relaxations in Undulating Channels

C. T. Combs, D. D. Seith, M. J. Bovyn, S. P. Gross, X. Xie, Z. S. Siwy

This study uses deep learning to classify cell sub-populations based on mechanical properties measured through deformability cytometry with high accuracy.

bioRxiv · May 17, 2021Biophysics