Justin Torok

The paper identifies presynaptic and postsynaptic risk genes and key connectomes involved in pathological α-synuclein spreading using mathematical models and gene regulatory network analysis.

The paper uses a network diffusion model to analyze how genetic factors and brain connectivity influence selective vulnerability or resilience to Alzheimer's tauopathy.

This study shows that directional bias in tau transmission along fiber tracts explains divergent spatiotemporal progression of tauopathies in mouse models.

This study uses mathematical models to analyze amyloid and tau interactions in Alzheimer's Disease, finding that a one-way amyloid-to-tau aggregation model best explains their spatiotemporal progression.

The paper identifies cell types and classes that confer vulnerability or resilience to tau pathology in Alzheimer's disease using single-cell RNA sequencing data and a cell-type mapping pipeline.

The paper introduces a computational pipeline called MISS to map diverse cell types in the murine brain using single-cell RNAseq and in situ hybridization data, showing improved accuracy through gene subset selection.

The paper develops a computational model of tau-modified axonal transport to show how directional biases in tau spread arise from transport feedback and conformation-specific dysregulation.

This study applies a seed-inference algorithm to Parkinson's Disease patients to show that atrophy patterns vary significantly between individuals and are better predicted by individualized seed locations than standard regions.