Alexandre Ferreira Ramos

The paper develops a framework to analyze thermodynamic models of transcriptional regulation using experimental data from Drosophila embryos.

The paper corrects claims that their solution for a self-repressing gene is incomplete and incorrect, showing the decaying rates are correct and the operator is self-adjoint with real eigenvalues.

The paper shows that bursty gene expression maximizes mutual information and reduces entropy in gene networks, suggesting it enhances reliability of communication in gene regulatory systems.

The paper presents a stochastic spatial model to simulate tumor growth with two cell phenotypes, showing it can reproduce Gompertz and bi-phasic growth dynamics.

The paper discusses the application of stochastic models to understand biological systems, focusing on gene expression and cell proliferation in cancer contexts.

The paper develops a two-state stochastic model for gene transcription in Drosophila embryos and shows it can produce bursts of varying sizes and durations, matching experimental data on eve gene stripe two formation.