3 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
Comparing AI versus Optimization Workflows for Simulation-Based Inference of Spatial-Stochastic Systems
Michael A. Ramirez-Sierra, Thomas R. Sokolowski
Model parameter inference is a universal problem across science. This challenge is particularly pronounced in developmental biology, where faithful mechanistic descriptions require…
AI-powered simulation-based inference of a genuinely spatial-stochastic model of early mouse embryogenesis
Michael A. Ramirez-Sierra, Thomas R. Sokolowski
Understanding how multicellular organisms reliably orchestrate cell-fate decisions is a central challenge in developmental biology. This is particularly intriguing in early mammali…
Stable developmental patterns of gene expression without morphogen gradients
Maciej Majka, Nils B. Becker, Pieter Rein ten Wolde +2
Gene expression patterns (GEPs) are established by cross-regulating target genes that interpret morphogen gradients. However, as development progresses, morphogen activity is reduc…
Deriving a genetic regulatory network from an optimization principle
Thomas R Sokolowski, Thomas Gregor, William Bialek +1
Many biological systems approach physical limits to their performance, motivating the idea that their behavior and underlying mechanisms could be determined by such optimality. Nev…