Characterising biochemical reaction network structure in mathematical terms enables the inference of functional biochemical consequences from network structure with existing mathematical techniques... Show moreCharacterising biochemical reaction network structure in mathematical terms enables the inference of functional biochemical consequences from network structure with existing mathematical techniques and spurs the development of new mathematics that exploits the peculiarities of biochemical network structure. The structure of a biochemical network may be specified by reaction stoichiometry, that is, the relative quantities of each molecule produced and consumed in each reaction of the network. A biochemical network may also be specified at a higher level of resolution in terms of the internal structure of each molecule and how molecular structures are transformed by each reaction in a network. The stoichiometry for a set of reactions can be compiled into a stoichiometric matrix N is an element of Z(mxn), where each row corresponds to a molecule and each column corresponds to a reaction. We demonstrate that a stoichiometric matrix may be split into the sum of m - rank(N) moiety transition matrices, each of which corresponds to a subnetwork accessible to a structurally identifiable conserved moiety. The existence of this moiety matrix splitting is a property that distinguishes a stoichiometric matrix from an arbitrary rectangular matrix. (C) 2020 Elsevier Ltd. All rights reserved. Show less
Drongelen, R. van; Vazquez-Faci, T.; Huijben, T.A.P.M.; Zee, M. van der; Idema, T. 2018
A key process in the life of any multicellular organism is its development from a single egg into a full grown adult. The first step in this process often consists of forming a tissue layer out of... Show moreA key process in the life of any multicellular organism is its development from a single egg into a full grown adult. The first step in this process often consists of forming a tissue layer out of randomly placed cells on the surface of the egg. We present a model for generating such a tissue, based on mechanical interactions between the cells, and find that the resulting cellular pattern corresponds to the Voronoi tessellation of the nuclei of the cells. Experimentally, we obtain the same result in both fruit flies and flour beetles, with a distribution of cell shapes that matches that of the model, without any adjustable parameters. Finally, we show that this pattern is broken when the cells grow at different rates. Show less
Fleming, R.M.; Vlassis, N.; Thiele, I.; Saunders, M.A. 2016
The possibilities of using a genetic algorithm for the prediction of RNA secondary structure were investigated. The algorithm, using the procedure of stepwise selection of the most fit structures ... Show moreThe possibilities of using a genetic algorithm for the prediction of RNA secondary structure were investigated. The algorithm, using the procedure of stepwise selection of the most fit structures (similarly to natural evolution), allows different models of fitness or driving forces determining RNA structure to be easily introduced. This can be used for simulation of the RNA folding process and for the investigation of possible folding pathways. Such an algorithm needs several modifications before it can predict RNA secondary structures. After modification, a fair number of correct stems are predicted, even when using computationally quick, but very crude, fitness criteria such as stem length and stacking energy, including elements of tertiary structure (pseudoknots). The fact that genetic algorithm simulation includes both stem formations and stem disruption allows one to observe intermediate structures that may be used in combination with phylogenetic or experimental research. Show less
