Author

Wai Lok Woo

Northumbria UniversityORCID 0000-0002-8698-7605Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:dimensionality reduction· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1

Frequent Co-Authors

Shiraz S KaderuppaniD· 2 shared Anurag SharmaiD· 1 shared Anurag SharmaiD· 1 shared Eugene· 1 shared Eugene Wai Leong WongiD· 1 shared Muhammad Ramadan SaifuddiniD· 1 shared Wong Wai Leong· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 13 mutual co-author links

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2 shared papersBioinformatics

Shiraz S KaderuppanORCID

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2 papers

Recent·Most cited

In silico prediction of cellular organelles from computationally super-resolved (SR) phase-modulated optical micrographs

Shiraz S Kaderuppan, Anurag Sharma, Muhammad Ramadan Saifuddin, Wong Wai Leong, Eugene, Wai Lok Woo

The paper develops deep neural networks to predict cellular organelles from super-resolved DIC and PCM micrographs, showing good correlation with ground truth images.

bioRxiv · Sep 14, 2025 · PreprintBioinformatics

{Theta}-Net: Achieving Enhanced Phase-Modulated Optical Nanoscopy in silico through a computational 'string of beads' architecture

Shiraz S Kaderuppan, Eugene Wai Leong Wong, Anurag Sharma, Wai Lok Woo

This paper introduces {Theta}-Net, a computational architecture that improves super-resolved optical microscopy images in silico, outperforming existing frameworks and demonstrating effectiveness under poor signal-to-noise ratios.

bioRxiv · Jan 24, 2023 · PreprintBioinformatics