3 citations · 3 across the 4 of their papers we have counts for
4 papers
Translating and evaluating single-cell Boolean network interventions in the multiscale setting
John Metzcar, Katie Pletz, Heber L. Rocha +1
Intracellular networks process cellular-level information and control cell fate. They can be computationally modeled using Boolean networks, which are implicit-time causal models o…
Modeling the extracellular matrix in cell migration and morphogenesis: A guide for the curious biologist
Rebecca M. Crossley, Samuel Johnson, Erika Tsingos +8
The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted. In processes of cell migration, the ECM also acts as…
A review of mechanistic learning in mathematical oncology
John Metzcar, Catherine R. Jutzeler, Paul Macklin +2
Mechanistic learning, the synergistic combination of knowledge-driven and data-driven modeling, is an emerging field. In particular, in mathematical oncology, the application of ma…
Accelerated solving of coupled, non-linear ODEs through LSTM-AI
Camila Faccini de Lima, Juliano Ferrari Gianlupi, John Metzcar +1
The present project aims to use machine learning, specifically neural networks (NN), to learn the trajectories of a set of coupled ordinary differential equations (ODEs) and decrea…