This improved consistency is valuable for planners who need predictions that can be trusted under all circumstances. Gene regulatory networks are essential for cell fate specification and function. But the recursive links that comprise these networks often make determining their properties and behaviour complicated; computational models of these networks can also be difficult to decipher. To reduce the complexity of such models Peter Sollich and colleagues employ a Zwanzig-Mori projection approach. This allows a system of ordinary differential equations, representing a network, to be reduced to an arbitrary subnetwork consisting of part of the initial network, with the rest of the network bulk captured by memory functions.
These memory functions account for the bulk by describing signals that return to the subnetwork after some time, having passed through the bulk. They show how this approach can be used to simplify analysis and to probe the behaviour of a gene regulatory network. Applying the method to a transcriptional network in the vertebrate neural tube reveals previously unappreciated properties of the network.
By taking advantage of the structure of the memory functions they identify interactions within the network that are unnecessary for sustaining correct patterning. Upon further investigation the authors find that these interactions are important for conferring robustness to variation in initial conditions.
Taken together they demonstrate the validity and applicability of the Zwanzig-Mori projection approach to gene regulatory networks. Metabolic enzyme cost explains variable trade-offs between microbial growth rate and. Berufsalltag der Heimhelferin. Mit Wissens-Check zu jedem Kapitel. Kumar; Lyn Denend; Thomas M. Christian Wittekind; Mary K.
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