Author

Amy Francis

University of BristolORCID 0009-0004-4807-1454Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Organism:human· 2 Research Focus:variant effect prediction· 2 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Colin CampbelliD· 2 shared Tom R. GauntiD· 2 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

2 top collaborators · 1 mutual co-author link

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2 shared papersGenomics

Colin CampbellORCID

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2 papers

Recent·Most cited

GenomicsBioinformatics AdvancesPeer-reviewedJan 1, 2026

CanDrivR-CS: A Cancer-Specific Machine Learning Framework for Distinguishing Recurrent and Rare Variants

Amy Francis, Colin Campbell, Tom R. Gaunt

CanDrivR-CS distinguishes recurrent and rare cancer variants using cancer-specific gradient boosting models, achieving high F1 scores in cross-validation.

DOI 10.1093/bioadv/vbag008

humanwhole-exome sequencing

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedMar 29, 2024

DrivR-Base: A Feature Extraction Toolkit For Variant Effect Prediction Model Construction

Amy Francis, Colin Campbell, Tom R. Gaunt

DrivR-Base extracts and integrates molecular features for variant effect prediction models using data from AlphaFold, ENCODE, and Variant Effect Predictor.

1 citation

humanwhole-genome sequencing

𝕏 PostBluesky