Renormalization Group Transformation for Hamiltonian Dynamical Systems in Biological Networks

2016/09/10 by Masamichi Sato, Sato, Masamichi · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #Dynamical Systems (math.DS) #FOS: Biological sciences #FOS: Mathematics #FOS: Physical sciences #Gene Regulatory Network Analysis #Nonlinear Dynamics and Pattern Formation #Other Quantitative Biology (q-bio.OT) #Protein Structure and Dynamics #cond-mat.dis-nn #math.DS #q-bio.OT

paper · pdf · doi:10.48550/arxiv.1609.02981

arxiv created 2016/09/10 · openalex publication_date 2016/09/10 · arxiv updated 2016/09/13 · openalex created_date 2016/09/23 · openalex updated_date 2026/07/28

Abstract

We apply the renormalization group theory to the dynamical systems with the simplest example of basic biological motifs. This includes the interpretation of complex networks as the perturbation to simple network. This is the first step to build our original framework to infer the properties of biological networks, and the basis work to see its effectiveness to actual complex systems.

Citations

• An exact mapping between the Variational Renormalization Group and Deep\n Learning

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