David A. J. Rand

The paper shows that RA induces a transient co-expression state of PAX6 and FOXA2 in neural tube organoids, leading to two opposing cell fates that determine cell-type proportions through feedback signaling.

The paper assesses the relationship between tumour circadian clock function and survival in breast cancer patients using a machine-learning model called TimeTeller, finding a negative association between clock function and survival.

The paper estimates the information content of developmental landscapes in two systems by integrating developmental biology, information theory, and dynamical systems.

This paper introduces a framework to model cell fate decisions using single-cell data, revealing conserved decision-making architectures across species.

TimeTeller estimates circadian clock function from single transcriptomes by modeling the multi-dimensional state of the clock, demonstrating its application across species and data types.

The paper develops a data-fitted landscape model for C. elegans vulval development using Catastrophe Theory and ABC, revealing a two-step decision process controlled by EGF and Notch-Delta signals.

The paper quantifies cell fate transitions during differentiation and identifies two mechanisms for binary cell fate decisions using a statistical model and experimental data.

This paper defines and mathematically characterizes multiplexing in signaling systems, provides experimental evidence for NF-κB's potential to multiplex information, and introduces new methods for analyzing dynamic models.

The paper introduces a new stochastic approximation method for analyzing large stochastic oscillators, providing accurate and fast simulation and inference tools.