Skip to main content

2 Result(s)

within Shushan Toneyan Remove this filter English Remove this filter Human Genetics Remove this filter

and

  1. No Access

    Article

    Current approaches to genomic deep learning struggle to fully capture human genetic variation

    Deep learning shows promise for predicting gene expression levels from DNA sequences. However, recent studies show that current state-of-the-art models struggle to accurately characterize expression variation ...

    Ziqi Tang, Shushan Toneyan, Peter K. Koo in Nature Genetics (2023)

  2. Article

    Open Access

    EvoAug: improving generalization and interpretability of genomic deep neural networks with evolution-inspired data augmentations

    Deep neural networks (DNNs) hold promise for functional genomics prediction, but their generalization capability may be limited by the amount of available data. To address this, we propose EvoAug, a suite of e...

    Nicholas Keone Lee, Ziqi Tang, Shushan Toneyan, Peter K. Koo in Genome Biology (2023)

    Download PDF (1482 KB) View Article