Author

Benyapa Insawang

The University of QueenslandORCID 0009-0009-8263-7454Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Alex William HewittiD· 1 shared Amitava DattaiD· 1 shared David Anthony MackeyiD· 1 shared Jamie E. CraigiD· 1 shared Max WardiD· 1 shared Puya GharahkhaniiD· 1 shared Richard Mills· 1 shared Stuart MacGregoriD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 18 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Alex William HewittORCID

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2 papers

Recent·Most cited

Genetic & Genomic MedicineInvestigative Ophthalmology & Visual SciencePeer-reviewedAug 17, 2026

Genome-wide association study of corneal dystrophy uncovers novel risk loci and enables improved polygenic prediction of Fuchs endothelial corneal dystrophy

Benyapa Insawang, David Anthony Mackey, Alex William Hewitt…·Stuart MacGregor

This paper identifies 24 risk loci for corneal dystrophy, constructs polygenic risk scores (PRS) and STR-based models, and shows PRS improves FECD prediction, while STR expansion is the strongest predictor.

DOI 10.1167/iovs.67.10.40

humanGWAS summary statistics

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BioinformaticsbioRxivPreprintOct 24, 2024

Classical statistical methods are powerful for the identification of novel targets for the survival of breast cancer patients

Benyapa Insawang, Max Ward, Zhaoyu Li, Amitava Datta

This study uses classical statistical methods to identify survival-related genes in breast cancer, finding two novel targets and validating results through bootstrapping.

DOI 10.1101/2024.10.24.620147

humanbulk RNA-seq

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