Barak Raveh

This paper introduces iMSMs to model biomolecular interactions, revealing kinetic states and transport pathways in nucleocytoplasmic transport.

CLIPepPI predicts domain-peptide specificity using contrastive learning, achieving competitive performance across benchmarks and enabling proteome-wide analysis.

DeepDynamics uses bulk RNA-seq and sc/snRNA-seq to infer cell-subtype and clinicopathological dynamics in Alzheimer's disease, identifying risk mediators in APOE4 carriers.

The paper constructs an integrative Brownian dynamics model of nucleocytoplasmic transport, revealing how FG repeat proteins and nuclear transport receptors mediate selective transport through NPCs.

This paper introduces Annotatability, a method that uses deep network training dynamics to identify and correct ambiguous cell annotations in single-cell and spatial omics data.

This paper introduces a Bayesian method to optimize metamodels for complex biological systems, showing improved accuracy in modeling beta-cell function in T2D.

The paper develops a Bayesian metamodel of pancreatic islet architecture and function by integrating imaging and physiological data with probabilistic graphical models and automation tools.