Aaron Clauset

This study shows that chemotherapy-induced senescence-associated secretome promotes metastasis in ovarian cancer by reprogramming metabolism and increasing cell detachment.

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.

STIX annotates structural variants using long-read data, achieving high accuracy and identifying common SVs in population-scale datasets.

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.

The paper quantifies how hiring and attrition affect gender diversity in U.S. academic faculty and models policy interventions to achieve gender parity.

This study uses machine learning to improve PCR success rates, achieving 81% prediction accuracy and identifying 15 under-optimized features.

This paper introduces network filters to reduce noise in large-scale biological data, improving accuracy in predicting protein expression changes in human tissues.