Jakob Träuble

NeuroSuite provides a non-invasive platform for long-term electrophysiological monitoring of brain organoids, revealing neural network development and activity changes.

The paper presents results from an open competition to develop aging biomarkers using DNA methylation data, showing improved predictive models for age, mortality, and multi-morbidity.

This study integrates multi-omic data from glioblastoma patients to identify a high-risk progenitor phenotype linked to poor survival and spatially defined tumor progression.

This paper uses contrastive learning on regional biomechanical properties from MRE to improve brain age prediction and detect neurodegeneration, finding that stiffness and damping ratio are sensitive biomarkers for Alzheimer's and MCI.

The paper introduces PseudoSort, a machine learning algorithm for spike sorting, and applies it to MEA data from hippocampal neurons exposed to monomeric Tau, revealing its impact on neuronal activity.