Juan F. Poyatos

The paper uses a transformer-based model to analyze zebrafish embryogenesis data, revealing network-level regulatory constraints during the phylotypic stage.

The paper develops a framework to analyze how malignant cellular states in pancreatic ductal adenocarcinoma relate to normal developmental trajectories, finding that while developmental programs help locate cancer states, they do not explain their diversification.

The paper introduces the [D]-[P] rule to quantify the relationship between developmental gene expression and phenotypic similarity, using C. elegans to show that genes with broad expression have systemic phenotypes and those with specific expression have specialized roles.

The paper redefines housekeeping genes to include those essential across developmental stages, not just adult tissues, using zebrafish data.

This paper combines gene regulation network models with polygenic prediction to explore how phenotypic variation can be captured using statistical methods, identifying key regulatory connections and linking findings to concepts like global sensitivity and epistasis.

The paper examines how protein length and amino acid costs influence gene expression in human cells and tissues, finding that cancer tissues overexpress cheap, compact genes.

The paper presents a framework using genome-scale metabolic reconstructions to interpret genotype-to-phenotype associations and identifies limitations in phenotype prediction in metabolism.

The paper develops a statistical framework to predict fitness costs of complex mutations by identifying key molecular predictors using RNA polymerase mutations in E. coli.

The paper introduces a computational method to assess tolerance to NADH/NAD+ redox imbalances in yeast, linking it to aging and anti-aging interventions.

The paper uses an in silico model of yeast metabolism to identify modifier genes that buffer or potentiate the effects of mutations on growth, revealing pleiotropy, epistasis, and environmental dependencies.

The paper quantifies how global transcriptional regulation affects gene expression across 700 genes in E. coli and shows that gene position near the origin of replication correlates with sensitivity to transcriptional resources.

The paper examines how genetic and epigenetic regulation deviates from a global transcriptional program in yeast under different nutrient conditions, identifying distinct regulatory strategies across gene classes.

This study investigates how dual autogenous control regulates the multiple antibiotic resistance phenotype in Escherichia coli, revealing mechanisms for rapid induction, pulse generation, and sensing range.