The lac operon in Escherichia coli has been studied extensively and is one of the earliest gene systems found to undergo both positive negative control. known exhibit bistability, sense that either induced or uninduced. Many dynamical models have proposed capture this phenomenon. While most are based on complex mathematical formulations, it suggested for other network topology sufficient produce desired behavior. We present a Boolean as discrete model operon. Our includes two main glucose...

Modeling stochasticity in gene regulatory networks is an important and complex problem molecular systems biology. To elucidate intrinsic noise, several modeling strategies such as the Gillespie algorithm have been used successfully. This article contributes approach alternative to these classical settings. Within discrete paradigm, where genes, proteins, other components of are modeled variables assigned logical rules describing their regulation through interactions with components....

An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network to logical and Petri nets. They used model a variety biochemical networks, such as metabolic gene regulatory networks signal transduction networks. There is evidence that can capture key dynamic features biological be successfully for hypothesis generation.This article provides unified framework aid the analysis models, represented polynomial dynamical systems, which...

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with goal finding strategies to change a disease or otherwise undesirable state biological system into another, more desirable, through an intervention, such drug therapeutic treatment. The identification is typically based on mathematical model process altered targeted inputs. This paper focuses processes at molecular level that determine individual cell, involving signaling gene...

A key problem in the analysis of mathematical models molecular networks is determination their steady states. The present paper addresses this for Boolean network models, an increasingly popular modeling paradigm lacking detailed kinetic information. For small can be solved by exhaustive enumeration all state transitions. But larger not feasible, since size phase space grows exponentially with dimension network. published growing to over 100, so that efficient methods are essential. Several...

Abstract Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical Petri nets, and agent-based to gain a better understanding of them. The computational complexity analyze the complete dynamics these models grows exponentially in number variables, which impedes working complex models. There exist software tools but they either lack algorithmic functionality deterministically or inaccessible many users require underlying...

Organisms and ecological groups accumulate evidence to make decisions. Classic experiments theoretical studies have explored this process when the correct choice is fixed during each trial. However, we live in a constantly changing world. What effect does such impermanence on classical results about decision making? To address question use sequential analysis derive tractable model of accumulation option changes time. Our shows that ideal observers discount prior at rate determined by...

Background Synthetic microbial consortia are conglomerations of genetically engineered microbes programmed to cooperatively bring about population‐level phenotypes. By coordinating their activity, the constituent strains can display emergent behaviors that difficult engineer into isogenic populations. To do so, communicate with one another through intercellular signaling pathways depend on cell density. Methods Here, we used computational modeling examine how behavior synthetic results from...

In a constantly changing world, animals must account for environmental volatility when making decisions. To appropriately discount older, irrelevant information, they need to learn the rate at which environment changes. We develop an ideal observer model capable of inferring present state along with its change. Key this computation is update posterior probability all possible change point counts. This can be challenging, as number possibilities grows rapidly time. However, we show how...

This paper addresses two topics in systems biology, the hypothesis that biological are modular and problem of relating structure function systems. The focus here is on gene regulatory networks, represented by Boolean network models, a commonly used tool. Most research modularity has focused structure, typically through either directed or undirected graphs. But since regulation highly dynamic process as it determines cells over time, natural to consider functional well. One main results...

Finite dynamical systems have been used successfully in modeling biological processes. When certain regulatory mechanisms of a system or model are unknown it is important to be able identify the best with available data. In this context, reverse engineering finite from partial information an problem. While problem has studied past, there currently no algorithms that can predict signs interactions. paper we propose framework and engineer possible signed wiring diagrams The algorithm consists...

In this manuscript we propose and implement a dimension reduction algorithm of AND-NOT networks for the purpose steady state computation. Our method network consists in using "steady approximations" that do not change number states. The is designed to work at wiring diagram level without need evaluate or simplify Boolean functions. Also, our implementation takes advantage sparsity typical discrete models biological systems. main features are it works preserves Furthermore, states original...

Synthetic gene oscillators are small, engineered genetic circuits that produce periodic variations in target protein expression. Like other circuits, synthetic noisy and exhibit fluctuations amplitude period. Understanding the origins of such variability is key to building predictive models can guide rational design circuits. Here, we developed a method for determining impact different sources noise by measuring oscillation correlations between sister cells. We first used combination...

.Due to cost concerns, it is optimal gain insight into the connectivity of biological and other networks using as few experiments possible. Data selection for unique network identification has been an open problem since introduction algebraic methods reverse engineering almost two decades. In this manuscript we determine what data sets uniquely identify unsigned wiring diagram corresponding a system that discrete in time space. Furthermore, answer question uniqueness signed diagrams Boolean...