Algebraic Biology: Second International Conference, AB 2007, by Bud Mishra (auth.), Hirokazu Anai, Katsuhisa Horimoto, Temur PDF

By Bud Mishra (auth.), Hirokazu Anai, Katsuhisa Horimoto, Temur Kutsia (eds.)

ISBN-10: 3540734325

ISBN-13: 9783540734321

This quantity constitutes the refereed court cases of the second one overseas convention on Algebraic Biology, held on the citadel of Hagenberg, Austria in July 2007. The convention was once run as a part of the study Institute for Symbolic Computation (RISC) summer season 2007.

Nineteen complete papers are provided, including 3 invited papers and 4 tutorials. each one paper has been rigorously reviewed via the book’s crew of specialist editors to make sure each meets the top criteria of analysis and scholarship.

The convention served as an interdisciplinary discussion board for the presentation of analysis on all elements of the appliance of symbolic computation in biology, together with laptop algebra, computational good judgment, and comparable tools. Papers additionally learn options to difficulties in biology utilizing symbolic methods.

Readers research new, leading edge methods to fixing difficulties in biology.

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Additional resources for Algebraic Biology: Second International Conference, AB 2007, Castle of Hagenberg, Austria, July 2-4, 2007. Proceedings

Example text

Siebert and A. Bockmayr The only information on a regulatory component we incorporate in the model for now is whether or not it is active. A vertex αi can be seen as a variable that adopts values in B, where the value 1 indicates that αi is active. To simplify notation, we identify each vertex αi with its index i. An edge αj → αi signifies that αj influences αi in a positive or negative way depending on the sign εij . For each αi we denote by P red(αi ) the set of predecessors of αi , i. , the set of vertices αj such that αj → αi is an edge in E.

Horimoto, and T. ): AB 2007, LNCS 4545, pp. 36–50, 2007. c Springer-Verlag Berlin Heidelberg 2007 Relating Attractors and Singular Steady States 37 impact of the threshold values, which they called singular values, would further improve the understanding of the system’s dynamics. In [8] they introduced the notion of singular steady states and linked them to feedback circuits in the interaction graph describing the structure of the network. The importance of feedback circuits for the analysis of the dynamical behavior has long been recognized.

Let I be an interaction graph comprising n vertices. A state of the system described by I is a tuple s ∈ B n . The set of (regular) resources Ri (s) = RiI (s) of αi in state s is the set {αj ∈ P red(αi ) | (εij = + ∧ sj = 1) ∨ (εij = − ∧ sj = 0)}. Given a set K(I) := {Ki,ω | i ∈ {1, . . , n}, ω ⊆ P red(αi )} of (logical) parameters, which adopt values in B, we define the Boolean function f = f K(I) : B n → B n , s → (K1,R1 (s) , . . , Kn,Rn (s) ). The pair N := (I, f ) is called bioregulatory network.

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Algebraic Biology: Second International Conference, AB 2007, Castle of Hagenberg, Austria, July 2-4, 2007. Proceedings by Bud Mishra (auth.), Hirokazu Anai, Katsuhisa Horimoto, Temur Kutsia (eds.)


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