Approaches to Complexity Reduction in a Systems Biology Research Environment (SYCAMORE)

Surovtsova,; Sable,; Pahle, Jürgen; Kummer,

doi:10.1109/wsc.2006.322943

Cited by 10 publications

(11 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, let us partition the species of the system into two sets X = ( X D , X C ), where X D represents the species in small numbers and X C the species in large numbers. Note that this partition is different from reaction based partitions used in other works [ 18 , 20 , 21 , 48 - 50 ]. All these works have as objective the reduction of simulation time.…”

Section: Methodsmentioning

confidence: 95%

Hybrid stochastic simplifications for multiscale gene networks

2009

View full text Add to dashboard Cite

Background: Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models.

show abstract

Section: Methodsmentioning

confidence: 95%

Hybrid stochastic simplifications for multiscale gene networks

2009

View full text Add to dashboard Cite

show abstract

“…Also, for large s, one can show that c + (s) % s and thus also c > e tot ; plainly, this is impossible because the concentration of enzyme bound in substrate cannot exceed that of the total enzyme. The solution c ) associated with the minus sign, on the other hand, can be recast in the form: The rightmost factor on the right-hand side of Eqn (20) is precisely the expression for the QSSA manifold; see Eqn (12). The coefficient R 1 (s), on the other hand, assumes moderate values and is close to 1 at large values of s, so that ZDP 1 lies close to the QSSA manifold for large s; this is plainly visible in Fig.…”

Section: Accurate Enzyme Kinetics Based On Zdpmentioning

confidence: 99%

“…These can be determined as described previously [44], and they express mathematically the fact that the total concentration of each of the four proteins is conserved. In particular, they are: [11,7] = Ñ [12,7] = Ñ [13,9]. Using these, we can expressz 6 ,z 8 ,z 10 andz 12 in terms of the remaining state variables, substitute these expressions in the original model, and obtain the nine-dimensional ODE system _ z ¼ NvðzÞ (final model).…”

Section: The Pts Modelmentioning

confidence: 99%

Simplified yet highly accurate enzyme kinetics for cases of low substrate concentrations

Härdin

Zagaris

Krab³

et al. 2009

The FEBS Journal

View full text Add to dashboard Cite

Much of enzyme kinetics builds on simplifications enabled by the quasi‐steady‐state approximation and is highly useful when the concentration of the enzyme is much lower than that of its substrate. However, in vivo, this condition is often violated. In the present study, we show that, under conditions of realistic yet high enzyme concentrations, the quasi‐steady‐state approximation may readily be off by more than a factor of four when predicting concentrations. We then present a novel extension of the quasi‐steady‐state approximation based on the zero‐derivative principle, which requires considerably less theoretical work than did previous such extensions. We show that the first‐order zero‐derivative principle, already describes much more accurately the true enzyme dynamics at enzyme concentrations close to the concentration of their substrates. This should be particularly relevant for enzyme kinetics where the substrate is an enzyme, such as in phosphorelay and mitogen‐activated protein kinase pathways. We illustrate this for the important example of the phosphotransferase system involved in glucose uptake, metabolism and signaling. We find that this system, with a potential complexity of nine dimensions, can be understood accurately using the first‐order zero‐derivative principle in terms of the behavior of a single variable with all other concentrations constrained to follow that behavior.

show abstract

“…This method has been applied to reduce Wnt/beta-catenin (62), NF-B (59), and glycolytic pathways (60,136). Another common reduction technique involves sensitivity analysis, which ascertains how parameter variation affects the system's response (135). This knowledge can be used to either eliminate insignificant contributions or aid in redesigning the model structure.…”

mentioning

confidence: 99%

The role of the hypothalamic-pituitary-adrenal axis in modulating seasonal changes in immunity

Pierre

Schlesinger

Androulakis

2016

Physiological Genomics

View full text Add to dashboard Cite

Seasonal changes in environmental conditions are accompanied by significant adjustment of multiple biological processes. In temperate regions, the day fraction, or photoperiod, is a robust environmental cue that synchronizes seasonal variations in neuroendocrine and metabolic function. In this work, we propose a semimechanistic mathematical model that considers the influence of seasonal photoperiod changes as well as cellular and molecular adaptations to investigate the seasonality of immune function. Our model predicts that the circadian rhythms of cortisol, our proinflammatory mediator, and its receptor exhibit seasonal differences in amplitude and phase, oscillating at higher amplitudes in the winter season with peak times occurring later in the day. Furthermore, the reduced photoperiod of winter coupled with seasonal alterations in physiological activity induces a more exacerbated immune response to acute stress, simulated in our studies as the administration of an acute dose of endotoxin. Our findings are therefore in accordance with experimental data that reflect the predominance of a proinflammatory state during the winter months. These changes in circadian rhythm dynamics may play a significant role in the seasonality of disease incidence and regulate the diurnal and seasonal variation of disease symptom severity.

show abstract

Approaches to Complexity Reduction in a Systems Biology Research Environment (SYCAMORE)

Cited by 10 publications

References 18 publications

Hybrid stochastic simplifications for multiscale gene networks

Hybrid stochastic simplifications for multiscale gene networks

Simplified yet highly accurate enzyme kinetics for cases of low substrate concentrations

The role of the hypothalamic-pituitary-adrenal axis in modulating seasonal changes in immunity

Contact Info

Product

Resources

About