Lucy B. Van Kleunen

This paper integrates multiple transcriptomics assays to identify cancer biomarkers, finding GBP4 as a predictor of recurrence and immune remodeling.

This study investigates the predictability of progression-free survival in ovarian cancer using NanoString gene expression data from pre- and post-chemotherapy samples, finding low predictability and suggesting the need for larger datasets.

The paper develops a stacked model to predict missing links in food webs using species traits and network structure, showing high accuracy on synthetic and real-world data.

This paper introduces a stacked model to predict missing links in under-sampled plant-pollinator networks using species traits and network topology, showing it can reconstruct networks and identify important features.

The paper uses spatial data from ovarian cancer tumors to show that spatial organization of the immune microenvironment correlates with patient outcomes and can predict treatment response.