Author

Mary‐Anne Hartley

École Polytechnique Fédérale de LausanneORCID 0000-0002-8826-3870Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Research Focus:database / resource· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Adam C. LevineiD· 1 shared Andrés ColubriiD· 1 shared August Felix· 1 shared Donald Samuel GrantiD· 1 shared Edward B. IrvineiD· 1 shared Evgeny M. ZdobnoviD· 1 shared Florian LaubscheriD· 1 shared Francisco BritoiD· 1 shared

Activity by Year

2019-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperBioinformatics

Adam C. LevineORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 18, 2026

CAPO: Compute-Aware Automated Protein-Model Optimization

Theo Schifferli, J. García Pardiñas, Edward B. Irvine…·Thomas Bikias

CAPO automates and selects protein-model adaptations by measuring feasibility and cost before training, improving performance while reducing compute usage and failures.

DOI 10.64898/2026.10.12.758406

protein sequencedeep learning

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BioinformaticsbioRxivPreprintMay 23, 2019

Novel Rhabdovirus and an almost complete drain fly transcriptome recovered from two independent contaminations of clinical samples.

Francisco Brito, Mosè Manni, Florian Laubscher…·Evgeny M. Zdobnov

The paper identifies a novel Rhabdovirus and a nearly complete drain fly transcriptome from contaminations in clinical samples, highlighting the importance of considering non-human sources in metagenomic analyses.

1 citation

metagenomicsstatistical model

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BioinformaticsEClinicalMedicinePeer-reviewedMay 1, 2019

Machine-Learning prognostic models from the 2014-16 Ebola outbreak: data-harmonization challenges, validation strategies, and mHealth applications

Andrés Colubri, Mary‐Anne Hartley, Matthew Siakor…·Pardis Christine Sabeti

The paper develops machine-learning prognostic models for Ebola virus disease using data from the 2014-16 outbreak, validated across independent datasets and integrated into a mobile health app.

60 citationstop 2%

machine learning (classical)benchmarking

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