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Eisuke Chikayama

Publications and source records attributed to Eisuke Chikayama.

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A Theory of Decomposition of Complex Chemical Networks using the Hill Functions

The design and synthesis of complex and large mimicked biochemical networks de novo is an unsolved problem in synthetic biology. To address this limitation without resorting to ad hoc computations and experiments, a predictive mathematical theory is required to reduce these complex chemical networks into natural physico-chemical expressions. Here we provide a theory that offers a physico-chemical expression for a large chemical network that is almost arbitrarily both nonlinear and complex. Unexpectedly, the theory demonstrates that such networks can be decomposed into reactions based solely on the Hill equation, a simple chemical logic gate. This theory, analogous to implemented electrical logic gates or functional algorithms in a computer, is proposed for implementing regulated sequences of functional chemical reactions, such as mimicked genes, transcriptional regulation, signal transduction, protein interaction, and metabolic networks, into an artificial designed chemical network.

physics.bio-ph

Decomposition of a Nonlinear Multivariate Function using the Heaviside Step Function

Whereas the Dirac delta function introduced by P. A. M. Dirac in 1930 in his famous quantum mechanics text has been well studied, a not famous formula related to the delta function using the Heaviside step function in a single-variable form, also given in Dirac's text, has been poorly studied. We demonstrate the decomposition of a nonlinear multivariate function into a sum of integrals in which each integrand is composed of a derivative of the function and a direct product of Heaviside step functions. It is an extension of Dirac's single-variable form to that for multiple variables. Moreover, it remains mathematically equivalent to the definition of the Dirac delta function with multiple variables, and offers a mathematically unified expression.

math.GM

Equations of Motion that Recognize Biochemical Patterns

Equations of motion that recognize biochemical patterns are described. The equations are partial differential equations in a continuous multiple component system in which adequate initial and boundary conditions are given. The biochemical patterns are spatiotemporal distributions of multiple biochemical components that can be regarded as a continuum in concentration and mass flux. Recognizing biochemical patterns lead to a universal property of the equations, which is also mathematically demonstrated, that the devised equations are sufficient to approximate any orbits in an arbitrary dynamical system, even though that of expectedly seen in complex biological systems. This theory can be applied to also a non-biological system that can be regarded as a continuum comprised of any multiple components such as liquids, solids, and nonlinear viscoelastic materials.

physics.bio-ph