Optimization algorithms to infer complex networks
Abstract
Symmetry is nature s deep design explaining from the fundamentalparticles and interactions in the universe to the structure of atoms,molecules and the phase transitions that emerge from states of matterYet, symmetry has not yet found widespread applicability to describeliving systems. This proposal will explore the appearance ofsymmetries in biological networks from the point of view ofpseudo-balanced coloring algorithms. We will focus on the study ofbiological networks spanning from the human brain network to generegulatory networks. We will explore the hypothesis that thecomplexity of this network is related to symmetry; this symmetrycaptures thecluster synchronization that is widespread in thesecomplex biological networks. We postulate a symmetry framework forbiological networks that accounts for how its structure determinesfunction. We will develop integer optimization algorithms that willallow to infer structural networks from cluster synchronization duringfunctional engagement of the network. Our findings will shed light tounderstanding how structure determines function from theoreticalprinciples. The project is under the auspice of the ResearchOpportunity for Program Officers program (ROPO).
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 09, 2024
- Source ID
- N000142412758
Entities
People
- Hernán A Makse
Organizations
- Office of Naval Research
- Research Foundation of The City University of New York
- United States Navy