Year: 2018
Type: article
Abstract: We present a new modeling and computational tool that computes rigorous summaries of network dynamics over large sets of parameter values. These summaries, organized in a database, can be searched for observed dynamics, e.g., bistability and hysteresis, to discover parameter regimes over which they are supported. We illustrate our approach on several networks underlying the restriction point of the cell cycle in humans and yeast. We rank networks by how robustly they support hysteresis, which is the observed phenotype. We find that the best 6-node human network and the yeast network share similar topology and robustness of hysteresis, in spite of having no homology between the corresponding nodes of the network. Our approach provides a new tool linking network structure and dynamics.
Source: PLoS Computational Biology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,043
Awards: G1092019292, G1484036585, G1816823653, INSPIRE: Nonlinear Data Reduction applied to Dense Granular Media, G2112585325, G2515541506, G3129816329, G4022875974, G4420254675, Collaborative Research: Computational and Data-Enabled Science and Engineering: Characterizing Dynamics of Particle-based Systems, G4713059963, G5270150132, G5520316217, G5636261911, CDI-TYPE II--COLLABORATIVE RESEARCH: Using Algebraic Topology to Connect Models with Measurements in Complex Nonequilibrium Systems, Impact of hepatocyte lineage life history dynamics on liver homeostasis in the ag, Emergent properties of synthetic microbial consortia, G668241585, G6948048155, Needle in a haystack: effective search for dynamics across the space of networks, Mathematical Models for Pause-induced Delays in Bioprocesses, G8852363705
OpenAlex ID: W2801926645