Algebraic Biology: Third International Conference, AB 2008, by Tatsuya Akutsu, Morihiro Hayashida, Takeyuki Tamura (auth.),

By Tatsuya Akutsu, Morihiro Hayashida, Takeyuki Tamura (auth.), Katsuhisa Horimoto, Georg Regensburger, Markus Rosenkranz, Hiroshi Yoshida (eds.)

This publication constitutes the refereed lawsuits of the 3rd overseas convention on Algebraic Biology, AB 2008, held on the fort of Hagenberg, Austria in July 2008 as a part of the RISC summer time 2008, geared up via the learn Institute for Symbolic Computation.

The 14 revised complete papers offered including three educational lectures have been rigorously reviewed and chosen from 27 submissions. The convention is the interdisciplinary discussion board for the presentation of analysis on all features of purposes of symbolic computation (computer algebra, computational good judgment, and similar equipment) to numerous matters in biology and lifestyles sciences in addition to different difficulties in biology being approached with symbolic methods.

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Additional resources for Algebraic Biology: Third International Conference, AB 2008, Castle of Hagenberg, Austria, July 31-August 2, 2008 Proceedings

Sample text

Then, according to the technique sketched in section 3, one gets an approximation of system (29) by replacing each expression Ai by a new dependent variable Fi (1 ≤ i ≤ n − 1) and by augmenting this system by the n − 1 following algebraic equations: 0 = ki+ P Pi − ki− Pi+1 , (1 ≤ i ≤ n − 1). (30) It is now sufficient to eliminate the Fi from the so obtained differential-algebraic system. Unfortunately, this cannot be performed by a standard differential elimination algorithm since the number of equations depends on the parameter n.

One thereby gets an exactly determined system of three linear equations whose unknowns are the parameters blocks. This system admits a unique solution. ) that the values of k12 , k21 and Ve also are uniquely defined. QED. In practice, the function x1 is known from a file of measures and one can try to numerically estimate the values of its first and its second derivative. If the measures are free of noise, the first derivative can be quite accurately estimated but this is usually not the case for the second derivative.

X ¨1 (x1 + ke )2 + [k12 + k21 ] x˙ 1 (x1 + ke )2 + [Ve ] x˙ 1 ke + [k21 Ve ] x1 (x1 + ke ) = 0. This equation tells us that the systems parameters are in principle uniquely defined. Indeed, assume that the function x1 is known. Then so are its derivatives x˙ 1 and x ¨1 . These three functions can therefore be evaluated for three different values of the time t. The known parameter ke can be replaced by its value. One thereby gets an exactly determined system of three linear equations whose unknowns are the parameters blocks.

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