Cell growth simulator: a user-friendly web server for growth balance analysis
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Computational models are essential for understanding the complex biochemical processes that govern cellular growth and metabolism. Growth Balance Analysis (GBA) provides a powerful framework for modeling cellular self-replication by incorporating metabolite concentrations and their non-linear influence on reaction kinetics. However, the complexity of implementing and solving such models has made them inaccessible to researchers without programming expertise. Here we present Cell Growth Simulator, a web-based application that enables efficient construction and analysis of GBA models through an intuitive interface and interactive visualizations. Cell growth simulator uses an intuitive spreadsheet interface, eliminating the need for coding, and integrates data from the BRENDA enzyme database to facilitate the incorporation of kinetic parameters. Cell growth simulator provides interactive visualizations, including customizable plots and dynamic metabolic pathway maps for interpreting optimization results. The platform makes nonlinear modeling of resource allocation in coarse-grained cellular systems accessible to a broader scientific audience, fostering interdisciplinary collaboration and advancing our understanding of cellular metabolism and growth. Cell growth simulator is freely available at: https://cellgrowthsim.com/ .
Author summary
We created Cell growth simulator to make modeling cellular self-replication and growth more accessible. Our goal was to create a web-based tool that helps researchers, regardless of their programming background, investigate how cells allocate their resources under realistic, nonlinear conditions. By focusing on a simplified framework that captures essential features of metabolism, we enable scientists to explore core principles of cellular growth, such as how proteins and metabolites interact to drive balanced growth.
Cell growth simulator provides a simple spreadsheet-like interface where users can build or import their models, eliminating the need for coding. Our application connects to a widely used enzyme database to help researchers select realistic parameter values, and provides interactive graphs and pathway maps to visualize and interpret results. By streamlining the complex mathematical steps involved in modeling and analysis, Cell growth simulator lowers technical barriers and encourages collaboration between biologists, computational scientists, and anyone interested in understanding how cells work. We hope it will serve as a valuable resource for studying metabolism and advancing our knowledge of cell growth.
