Julia Åkesson

Protein-protein interaction priors shape biologically coherent latent spaces for causally concordant cross-omic translation

This paper introduces a PPI prior to guide autoencoder embeddings, improving biological coherence and downstream task performance in multi-omic data.

System-level health profiling from blood DNA methylation with explainable deep learning

The paper develops an explainable deep learning framework to predict health scores from blood DNA methylation, showing strong predictive accuracy and alignment with biological processes.

ComHub: Community predictions of hubs in gene regulatory networks

ComHub predicts hub transcription factors in gene regulatory networks by averaging predictions from multiple network inference methods, showing robust performance on benchmark datasets.