Author

S. Sakata

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 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:dimensionality reduction· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:deconvolution· 1 Assay:fluorescence / live-cell microscopy· 1

Frequent Co-Authors

K. Dholakia· 2 shared P. Wijesinghe· 2 shared S. Corsetti· 2 shared B. Bernard· 1 shared B. Carter· 1 shared C. Chen· 1 shared C. S. Herrington· 1 shared C. Sievers· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersBiophysics

K. Dholakia

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Epigenetic silencing by SMYD3 represses tumor intrinsic interferon response in HPV-negative squamous cell carcinoma of the head and neck.

N. Nigam, B. Bernard, S. Kim, K. Burkitt, D. Tsai, Y. Robbins, C. Sievers, C. T. Allen, R. L. Bennett, T. T. Tettey, B. Carter, R. Bao, L. Rinaldi, M. W. Lingen, H. Sater, , V. Saloura

This study identifies SMYD3 as an epigenetic regulator that suppresses the intrinsic interferon response in HPV-negative HNSCC, offering a potential strategy to enhance immunotherapy response.

bioRxiv · Nov 4, 2022 · PreprintCancer Biology

Experimentally unsupervised deconvolution for light-sheet microscopy with propagation-invariant beams

P. Wijesinghe, S. Corsetti, D. J. X. Chow, S. Sakata, K. Dunning, K. Dholakia

This paper introduces a deep learning deconvolution method for light-sheet microscopy using propagation-invariant beams, trained with physics-based images and unpaired data, achieving improved image contrast without requiring extensive paired training data.

bioRxiv · May 26, 2021Biophysics

Widefield light sheet microscopy using an Airy beam combined with deep-learning super-resolution

S. Corsetti, P. Wijesinghe, P. B. Poulton, S. Sakata, K. Vyas, C. S. Herrington, J. Nylk, F. Gasparoli, K. Dholakia

This paper introduces a method combining an Airy beam and deep-learning super-resolution to enhance resolution and field of view in light-sheet microscopy, demonstrating improvements in imaging biological samples.

bioRxiv · Feb 27, 2020Biophysics