Author

Figali Taho

BC Cancer Agency

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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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:protein design· 1 Assay:protein sequence· 1

Frequent Co-Authors

Caren C. HelbingiD· 1 shared Caroline E. CameroniD· 1 shared Chen YangiD· 1 shared Chenkai LiiD· 1 shared Darcy SutherlandiD· 1 shared İnanç BiroliD· 1 shared Lauren C. Bergman· 1 shared Linda HoangiD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Caren C. HelbingORCID

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1 paper

Recent·Most cited

AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens

Chenkai Li, Darcy Sutherland, S. Austin Hammond, Chen Yang, Figali Taho, Lauren C. Bergman, Simon Houston, René L. Warren, Titus Wong, Linda Hoang, Caroline E. Cameron, Caren C. Helbing, İnanç Birol

AMPlify is a deep learning model that predicts antimicrobial peptides from bullfrog genomes, identifying novel peptides effective against WHO priority pathogens including drug-resistant bacteria.

BMC Genomics · Jan 25, 2022Peer-reviewedBioinformatics