This chapter presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for evolutionary synthetic gene networks in synthetic biology.
The relative simplicity of the organisation of the olfactory system, the speed and robustness of these forms of social learning together with the similarity in brain regions and neurochemical contributions across the different learning paradigms make them important and useful models for investigating general principles of learning and memory in the brain.
Indeed, since human speech and learned vocalizations in songbirds bear behavioural and neural parallels, songbirds provide a genuine model for investigating the basic principles of speech and its pathologies [43], [44].
Given that Lam6 is part of a large protein family and is conserved in vertebrates, our work opens avenues for investigating the underlying principles of organelle communication.
These three groups of neurons have extensive interconnectivity and indeed, the antennal lobe has emerged as a model neural circuit for investigating the general principles of information processing (Wang, 2012; Wilson, 2013; Twick et al., 2014).
Thus, it is very important and necessary for investigating and developing principle approaches and flexible tools to allow individuals to collaboratively build, refine, and integrate existing ontologies.
Pimsner C*-algebras furnish a framework for investigating the variational principle, which asserts the equality of Pθ(a) with the supremum of the free energies over all θ -invariant states.
By providing a unifying principle for biology, evolution provides a powerful framework for investigating the living world, enabling us to develop models, frame theories, and test hypotheses.
In this study, we provide a proof-of-principle that iPSC technology can provide a valuable platform for investigating gene therapeutic approaches in CGD.
