Author

Sarath Chandar

Canadian Institute for Advanced ResearchORCID 0000-0002-9678-2830Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:machine learning (classical)· 2 Research Focus:protein structure prediction· 2 Approach:statistical model· 2 Assay:metagenomics· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Quentin FournieriD· 3 shared CHRISTOPHER JAMES LANGMEADiD· 2 shared Robert McCoy VernoniD· 2 shared Alex Aselstyne· 1 shared Almer M. van der SlootiD· 1 shared Benjamin Schulz· 1 shared David Heurtel-Depeiges· 1 shared Douglas C. Millar· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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3 shared papersBioinformatics

Quentin FournierORCID

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Author profile →

3 papers

Recent·Most cited

pLM representations unlock metagenomic space beyond homology

Lola Le Breton, David Heurtel-Depeiges, Douglas C. Millar, Lara E. Zetzsche, Robert McCoy Vernon, CHRISTOPHER JAMES LANGMEAD, Sarath Chandar, Quentin Fournier

This paper shows that protein language models can better annotate metagenomic proteins when trained on curated data, enabling retrieval of diverse enzyme candidates from billions of sequences.

bioRxiv · Jul 30, 2026 · PreprintBioinformatics

A systematic analysis of machine learning pipelines for robust antimicrobial resistance prediction

Alex Aselstyne, Enamundram Naga Karthik, Meriem El Azami, Romain Pogorelcnik, Quentin Fournier, Sarath Chandar

This study evaluates ML pipelines for AMR prediction using genomic data, identifying key factors affecting performance and supporting tree-based models.

bioRxiv · Jul 8, 2026 · PreprintBioinformatics

Protein Language Models: Is Scaling Necessary?

Quentin Fournier, Robert McCoy Vernon, Almer M. van der Sloot, Benjamin Schulz, Sarath Chandar, CHRISTOPHER JAMES LANGMEAD

This paper introduces AMPLIFY, a protein language model that achieves better performance with less training cost by improving data quality and architecture, challenging the need for scaling.

bioRxiv · Sep 23, 2024 · PreprintMolecular Biology