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Multi-level model-coupling of complex systems: application to biological systems.
, 2017 Dorra Louati
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Moving beyond diagnostic labels in psychiatry: outcome-linked treatment modelling. [PDF]
Gen PsychiatrLyndon S.
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Tumour-on-Chip Models for the Study of Ovarian Cancer: Current Challenges and Future Prospects. [PDF]
Cancers (Basel)Lim SY, Aboelnasr LS, El-Bahrawy M.
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A proposed method for estimating habitat suitability of weed biological control agents with experimentally derived thermal injury and weather data. [PDF]
Environ EntomolKnight IA +5 more
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Electronics and Power, 1971
Co-operation between control engineers and biologists can help in the understanding of both biological and control systems.
F.R. Janes, E.R. Carson
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Co-operation between control engineers and biologists can help in the understanding of both biological and control systems.
F.R. Janes, E.R. Carson
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2010
What are the mechanisms underlying biological systems’ ability to transform themselves: the ability of structures to replicate for their own goals, or to meet the specific goals of the system or environment to which they belong? What kind of evolutionary process underlies the emergence of the simple structures which joined together and replicated to ...
Eleonora Bilotta, Pietro Pantano
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What are the mechanisms underlying biological systems’ ability to transform themselves: the ability of structures to replicate for their own goals, or to meet the specific goals of the system or environment to which they belong? What kind of evolutionary process underlies the emergence of the simple structures which joined together and replicated to ...
Eleonora Bilotta, Pietro Pantano
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1990
Biological systems are complex systems, almost by definition. Thus models of such systems necessarily simplify. That even simple models can lead to very complicated behaviour leads us to re-examine the goal of mathematical modelling. We may distinguish two loose categories of model: the “pure” model whose end is the understanding of phenomena, and the “
M. Deakin
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Biological systems are complex systems, almost by definition. Thus models of such systems necessarily simplify. That even simple models can lead to very complicated behaviour leads us to re-examine the goal of mathematical modelling. We may distinguish two loose categories of model: the “pure” model whose end is the understanding of phenomena, and the “
M. Deakin
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