Author

T. Sengupta

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 Bioengineering· 1 Cell Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Organism:C. elegans· 2 Research Focus:cell type annotation· 1 Research Focus:deconvolution· 1 Research Focus:development & morphogenesis· 1 Research Focus:dimensionality reduction· 1 Organism:Drosophila· 1 Approach:experimental assay· 1

Frequent Co-Authors

D. Colon-Ramos· 2 shared H. Shroff· 2 shared J. Liu· 2 shared R. Christensen· 2 shared X. Han· 2 shared Y. Su· 2 shared Y. Wu· 2 shared A. Patel· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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2 shared papersBiophysics

D. Colon-Ramos

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Enhanced Branched-Chain Amino Acid Metabolism Improves Age-related Reproductive Function

C. Lesnik, R. Kaletsky, J. Ashraf, S. Sohrabi, V. Cota, T. Sengupta, W. Keyes, S. Luo, C. T. Murphy

This study shows that enhancing branched-chain amino acid metabolism improves reproductive function in aging C. elegans by maintaining oocyte quality.

bioRxiv · Feb 9, 2023Cell Biology

Incorporating the image formation process into deep learning improves network performance in deconvolution applications

Y. Li, Y. Su, M. Guo, X. Han, J. Liu, H. Vishwasrao, X. Li, R. Christensen, T. Sengupta, M. Moyle, J. Chen, T. B. Usdin, D. Colon-Ramos, H. Liu, Y. Wu, H. Shroff

This paper introduces RLN, a deep learning method for 3D fluorescence microscopy deconvolution that improves speed, performance, and generalizability compared to existing methods.

bioRxiv · Mar 5, 2022 · PreprintBiophysics

Multiview super-resolution microscopy

Y. Wu, X. Han, Y. Su, M. Glidewell, J. S. Daniels, J. Liu, T. Sengupta, I. Rey-Suarez, R. Fischer, A. Patel, C. Combs, J. Sun, X. Wu, R. Christensen, C. Smith, , H. Shroff

This paper introduces a multiview super-resolution microscopy approach that enhances confocal microscopy resolution and reduces phototoxicity across multiple scales.

bioRxiv · May 21, 2021 · PreprintBioengineering

Effect of Variations in the Conserved Residues E371 and S359 on the Structural Dynamics of Protein Z Dependent Protease Inhibitor (ZPI): A Molecular Dynamic Simulation Study

S. Chellam Gayathri, S. Gupta, A. Suresh, S. Senapati, T. Sengupta

This study uses molecular dynamics simulations to analyze how mutations at conserved residues E371 and S359 affect the structural dynamics of ZPI, revealing their role in RCL flexibility and protease inhibition.

bioRxiv · Dec 2, 2020Biophysics