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The authors do not make an explicit distinction between computable models and computational tools.
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They typically convert interaction networks into computable models and then train the models against experimental data [ 9, 14- 16].
Perhaps there are no better examples than the penetration of mathematics and computable models into biology and living systems.
The implementation of computable models with reciprocity within and between levels of biological organization (i.e. essential nesting) is central for studying antibiotic resistances.
Knowledge representation is the application of logic and ontology to build computable models for various domains [8].
A final important point about computable models is the importance of correctly identifying, understanding and documenting approximations.
Computable models can be expressed in any Turing-complete formal language, and in particular in any of the commonly used programming languages, making them the most precise and unambiguous scientific models.
Computable models are the models that are of prime interest in computational science.
Medical knowledge representation and management is concerned with how to organise the often vague clinical experience of medical staff required for computable models.
Moreover, as explained above, computable models actually require a Turing-complete notation.
Computable models can be expressed unambiguously in a Turing-complete formal language.
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