Author

Pierre-Aurélien Gilliot

University of BristolORCID 0000-0003-2542-2472Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:DNA methylation· 1 Organism:E. coli· 1 Research Focus:protein structure prediction· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Thomas E. GorochowskiiD· 2 shared

Activity by Year

2023-2024 · peak 1/yr

2 papers

Recent·Most cited

Synthetic BiologyNucleic Acids ResearchPeer-reviewedMay 28, 2024

Transfer learning for cross-context prediction of protein expression from 5'UTR sequence

Pierre-Aurélien Gilliot, Thomas E. Gorochowski

This paper uses transfer learning to adapt a deep learning model for predicting protein expression from 5'UTR sequences across different experimental contexts in E. coli.

11 citations

E. coliDNA methylation

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Synthetic BiologyBioinformaticsPeer-reviewedApr 21, 2023

Effective design and inference for cell sorting and sequencing based massively parallel reporter assays

Pierre-Aurélien Gilliot, Thomas E. Gorochowski

This paper develops FORE-CAST, a Python package for simulating and analyzing MPRAs to improve experimental design and inference of genetic function.

10 citations

statistical modelbenchmarking

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