Author

Alexandre Templier

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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Genomics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:metagenomics· 1

Frequent Co-Authors

Edi PriftiiD· 1 shared Jean‐Daniel ZuckeriD· 1 shared Maxence QueyreliD· 1 shared

Activity by Year

2020-2020 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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1 shared paperGenomics

Edi PriftiORCID

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1 paper

Recent·Most cited

Towards end-to-end disease prediction from raw metagenomic data

Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean‐Daniel Zucker

This paper introduces metagenome2vec, an end-to-end deep learning approach that classifies diseases from raw metagenomic reads, achieving performance comparable to conventional pipelines.

bioRxiv · Oct 29, 2020 · PreprintGenomics