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A scientific model seeks to represent empirical objects, phenomena, and physical processes in a logical and objective way. All models are in simulacra, that is, simplified reflections of reality that, despite being approximations, can be extremely useful. [6] Building and disputing models is fundamental to the scientific enterprise.
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.
Animal models observed in the sciences of psychology and sociology are often termed animal models of behavior. It is difficult to build an animal model that perfectly reproduces the symptoms of depression in patients. Depression, as other mental disorders, consists of endophenotypes [83] that can be reproduced independently and evaluated in ...
Model of a molecule, with coloured balls representing different atoms. A model is an informative representation of an object, person, or system. The term originally denoted the plans of a building in late 16th-century English, and derived via French and Italian ultimately from Latin modulus, a measure.
One can use language to describe a model; however, the theory is the model (or a collection of similar models), and not the description of the model. A model of the solar system, for example, might consist of abstract objects that represent the sun and the planets. These objects have associated properties, e.g., positions, velocities, and masses.
One of the popular examples in computer science is the mathematical models of various machines, an example is the deterministic finite automaton (DFA) which is defined as an abstract mathematical concept, but due to the deterministic nature of a DFA, it is implementable in hardware and software for solving various specific problems. For example ...
The complexity of systems addressed by microscale models leads to complexity in the models themselves, and the specification of a microscale model can be tens or hundreds of times larger than its corresponding macroscale model. (The simplified example of Figure 2 has 25 times as many lines in its specification as does Figure 1.)
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.