Inferring local molecular dynamics from the global actin network structure: A case study of 2D synthetic branching actin networks

Minghao W. Rostami, Brittany E. Bannish, Kelsey Gasior, Rebecca L. Pinals, Calina Copos, Adriana T. Dawes

Research output: Contribution to journalArticlepeer-review


Cells rely on their cytoskeleton for key processes including division and directed motility. Actin filaments are a primary constituent of the cytoskeleton. Although actin filaments can create a variety of network architectures linked to distinct cell functions, the microscale molecular interactions that give rise to these macroscale structures are not well understood. In this work, we investigate the microscale mechanisms that produce different branched actin network structures using an iterative classification approach. First, we employ a simple yet comprehensive agent-based model that produces synthetic actin networks with precise control over the microscale dynamics. Then we apply machine learning techniques to classify actin networks based on measurable network density and geometry, identifying key mechanistic processes that lead to particular branched actin network architectures. Extensive computational experiments reveal that the most accurate method uses a combination of supervised learning based on network density and unsupervised learning based on network symmetry. This framework can potentially serve as a powerful tool to discover the molecular interactions that produce the wide variety of actin network configurations associated with normal development as well as pathological conditions such as cancer.

Original languageEnglish (US)
Article number111613
JournalJournal of Theoretical Biology
StatePublished - Nov 7 2023
Externally publishedYes


  • Actin
  • Agent-based model
  • Branched actin network
  • Cell cytoskeleton
  • Lamellipodium
  • Machine learning

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics


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