B-BIND: Biophysical Bayesian Inference forNeurodegenerative Dynamics (Updated July 31, 2024).

A preprint abstract discusses the challenges of inferring the underlying disease state in Alzheimer's Disease (AD) progression. The paper proposes a biophysically motivated Bayesian framework called B-BIND, which models the disease state and continuously infers it from observed quantifications of multiple AD pathological proteins. The framework assigns a latent score, called pseudotime, to each pathological state, creating a pseudotemporal order of donors based on their pathological burden. The paper provides estimation algorithms and applies the methodology to data from the Seattle Alzheimer's Disease Brain Cell Atlas. This research lays the groundwork for continuous pseudotime modeling in the analysis of neurodegenerative diseases. [Extracted from the article]