Gustavo S. Jeuken

The paper shows that degree bias in phage-host networks inflates ML model performance and proposes a method to improve predictions by removing this bias.

Moirai infers cell trajectories by focusing on gene-level expression dynamics, improving detection of branching points in developmental processes.

CycleVI isolates cell cycle variation in scRNA-seq data using a deep generative model, improving the resolution of biological processes and drug response signals.

The paper introduces MIPath, a pathway analysis method using mutual information to assess pathway-phenotype associations with fewer assumptions, showing better performance on single-cell datasets.

The paper uses pathway activity estimated via singular value decomposition to predict survival time in breast cancer patients, finding it more prognostic than individual transcripts.