Author

Jimmy Royer

Analysis Group (United States)ORCID 0000-0003-3727-1069Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Organism:human· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Akshith DoddiiD· 1 shared Andrew L. BeamiD· 1 shared Isaac S. KohaneiD· 1 shared Luca FreschiiD· 1 shared Maha Reda FarhatiD· 1 shared Marco L. SchitoiD· 1 shared Matthew N. Ezewudo· 1 shared Michael L. CheniD· 1 shared

Activity by Year

2019-2019 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperBioinformatics

Akshith DoddiORCID

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1 paper

Recent·Most cited

Deep learning predicts tuberculosis drug resistance status from genome sequencing data

Michael L. Chen, Akshith Doddi, Jimmy Royer, Luca Freschi, Marco L. Schito, Matthew N. Ezewudo, Isaac S. Kohane, Andrew L. Beam, Maha Reda Farhat

This study uses a multitask deep learning model to predict tuberculosis drug resistance from genomic data, achieving high accuracy in both first-line and second-line drug resistance prediction.

EBioMedicine · Apr 29, 2019Peer-reviewedBioinformatics