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bioRxiv · 10.64898/2026.04.19.719454

Expanding P-NET, a multi-purpose biologically informed deep learning framework

Elmarakeby, H.·Glettig, M.·Zhou, A.·Zhou, C.·Tarantino, G.·Aprati, T.·Van Allen, E.·Liu, D.
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Abstract

We present expanded P-NET, a versatile frame-work for deep learning in computational biology based on P-NET, leveraging biological pathways for interpretable predictions. Our framework achieves competitive performance in genomic & transcriptomic prediction tasks. We demonstrate its stability and interpretability compared to traditional machine learning models. P-NET 2.0 incorporates gene and pathway information, providing valuable insights into complex biological processes. The framework is publicly available, enabling its application to various computational biology tasks.

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Elmarakeby, H., Glettig, M., Zhou, A., Zhou, C., Tarantino, G., Aprati, T., Van Allen, E., Liu, D.. 2026-04-22. Expanding P-NET, a multi-purpose biologically informed deep learning framework. https://doi.org/10.64898/2026.04.19.719454

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