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Laura Rumpf

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Open access Jul 2026

Comparing machine learning methods predicting transcriptome from epigenome with applications to association studies

This work provides a foundation for applications that link epigenome variation to gene expression in human cells, by benchmarking methods on a per-gene basis, illustrating their use in a disease context and making trained models available to the community.

Fatemeh Behjati Ardakani, Shamim Ashrafiyan, Laura Rumpf et al. · 0 citations