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Open Access

Peer-reviewed

Research Article

Machine Learning approaches for the detection of disease-causing variants in whole-genome data need to address the expression of functional genes

Camilla Mapstone,

Roles Data curation, Formal analysis, Investigation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
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Julia Handl,

Roles Conceptualization, Supervision, Writing – review & editing

Affiliation Alliance Manchester Business School, The University of Manchester, Manchester, United Kingdom
⨯
David Talavera

Roles Conceptualization, Investigation, Supervision, Writing – original draft, Writing – review & editing

* E-mail: David.Talavera@manchester.ac.uk

Affiliation Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom

https://orcid.org/0000-0002-8820-3931

⨯

Machine Learning approaches for the detection of disease-causing variants in whole-genome data need to address the expression of functional genes

Camilla Mapstone,
Julia Handl,
David Talavera

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Published: August 28, 2026
https://doi.org/10.1371/journal.pone.0355557

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