A field studying how interactions among biological components generate system-level behavior, using quantitative measurements, perturbations and mathematical models.
Computational integration of an organism’s interacting physiological and developmental processes at a stated resolution and for a stated range of conditions.
A collaborative project for integrating computational descriptions of Caenorhabditis elegans. It makes whole-organism modeling concrete by connecting cellular and physiological components; the project’s scope does not imply that every biological event is already simulated.[ref]
Integration of models of several cellular processes into one computational description of a biological cell. In a model of Mycoplasma genitalium, coupling processes made their shared molecular resources and timing experimentally testable. Whole-cell describes intended coverage, not complete knowledge of every event.[ref]
A whole-cell computational model predicts phenotype from genotype by Jonathan R. Karr and others. Summary and model integration
Coupling models at different spatial or temporal resolutions while making their interfaces, units and conservation requirements explicit.
Equation-free modeling performs coarse-scale calculations using short runs of a finer-scale simulator when an explicit coarse evolution equation is unavailable. A lifting step constructs microscopic states consistent with coarse variables; simulation advances them; restriction measures the resulting coarse state. These operations define a coarse time-stepper. [ref]
Equation-Free, Coarse-Grained Multiscale Computation: Enabling Microscopic Simulators to Perform System-Level Analysis by Yannis G. Kevrekidis and others. 2003, lifting, restriction and coarse time-stepper framework
For example, microscopic cell states can be initialized to match a population density, evolved briefly, and averaged to estimate a coarse change rate. That estimate can feed a longer projective step or a steady-state calculation. The method needs suitable coarse variables and separation between fast relaxation and slow evolution. If unresolved memory remains important, two microscopic preparations with the same coarse value can evolve differently, invalidating the assumed closure.
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Systems biology is an interdisciplinary field that focuses on the complex interactions within biological systems, integrating various biological data and approaches to understand the dynamics of these systems as a whole. Rather than studying individual components in isolation—such as genes, proteins, or metabolic pathways—systems biology seeks to understand how these components interact with each other and how they contribute to the overall behavior of biological organisms.
