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A biological model is an organism or system representing a more complex biological entity. It may refer to: a model organism, a non-human species that is extensively studied to understand particular biological phenomena present in many related organisms; an in vitro model system, representing complex in vivo systems; a mathematical model of a ...
Modelling biological systems is a significant task of systems biology and mathematical biology. [ a ] Computational systems biology [ b ] [ 1 ] aims to develop and use efficient algorithms , data structures , visualization and communication tools with the goal of computer modelling of biological systems.
A model of a biological system is converted into a system of equations, although the word 'model' is often used synonymously with the system of corresponding equations. The solution of the equations, by either analytical or numerical means, describes how the biological system behaves either over time or at equilibrium. There are many different ...
A model organism is a non-human species that is extensively studied to understand particular biological phenomena, with the expectation that discoveries made in the model organism will provide insight into the workings of other organisms.
Systems biology is the computational and mathematical analysis and modeling of complex biological systems.It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach (holism instead of the more traditional reductionism) to biological research.
The bioecological model of development is the mature and final revision of Urie Bronfenbrenner's ecological system theory. The primary focus of ecological systems theory is on the systemic examination of contextual variability in development processes.
Stentor coeruleus, used in molecular biology (its genome has been sequenced), [5] and is studied as a model of single-cell regeneration.; Dictyostelium discoideum, used in molecular biology and genetics (its genome has been sequenced), and is studied as an example of cell communication, differentiation, and programmed cell death.
While this model has seen success in machine-learning applications, it is a poor model for real (biological) neurons, because it lacks time-dependence in input and output. When an input is switched on at a time t and kept constant thereafter, biological neurons emit a spike train.