Ernst C. Wit

This paper develops a statistical model to infer hematopoietic stem cell dynamics in a gene therapy trial for Wiskott-Aldrich Syndrome and finds evidence for a myeloid-based developmental pathway.

This paper develops a stochastic framework to model cell differentiation networks from noisy clonal tracking data, providing tools for analyzing gene therapy studies.

The paper introduces a stochastic model to detect clonal dominance in gene therapy by comparing base and extended models using AIC on clonal tracking data.

The paper introduces PCgen, an algorithm that reconstructs genetic networks by incorporating direct and indirect effects, improving accuracy using individual data over genotypic means.

MAGMA infers microbial association networks by accounting for microbiota data features like zeros, overdispersion, and covariates, outperforming existing methods in simulations and revealing new biology in real data.