Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Stochastic kinetics on networks: when slow is fast.

ABSTRACT: Most chemical and biological processes can be viewed as reaction networks in which different pathways often compete kinetically for transformation of substrates into products. An enzymatic process is an example of such phenomena when biological catalysts create new routes for chemical reactions to proceed. It is typically assumed that the general process of product formation is governed by the pathway with the fastest kinetics at all time scales. In contrast to the expectation, here we show theoretically that at time scales sufficiently short, reactions are predominantly determined by the shortest pathway (in the number of intermediate states), regardless of the average turnover time associated with each pathway. This universal phenomenon is demonstrated by an explicit calculation for a system with two competing reversible (or irreversible) pathways. The time scales that characterize this regime and its relevance for single-molecule experimental studies are also discussed.

SUBMITTER: Li X

PROVIDER: S-EPMC4154737 | biostudies-other | 2014 Sep

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

Stochastic rectification of fast oscillations on slow manifold closures.

Project description:The problems of identifying the slow component (e.g., for weather forecast initialization) and of characterizing slow-fast interactions are central to geophysical fluid dynamics. In this study, the related rectification problem of slow manifold closures is addressed when breakdown of slow-to-fast scales deterministic parameterizations occurs due to explosive emergence of fast oscillations on the slow, geostrophic motion. For such regimes, it is shown on the Lorenz 80 model that if 1) the underlying manifold provides a good approximation of the optimal nonlinear parameterization that averages out the fast variables and 2) the residual dynamics off this manifold is mainly orthogonal to it, then no memory terms are required in the Mori-Zwanzig full closure. Instead, the noise term is key to resolve, and is shown to be, in this case, well modeled by a state-independent noise, obtained by means of networks of stochastic nonlinear oscillators. This stochastic parameterization allows, in turn, for rectifying the momentum-balanced slow manifold, and for accurate recovery of the multiscale dynamics. The approach is promising to be further applied to the closure of other more complex slow-fast systems, in strongly coupled regimes.

| S-EPMC8640743 | biostudies-literature

Multi-modality in gene regulatory networks with slow promoter kinetics.

Project description:Phenotypical variability in the absence of genetic variation often reflects complex energetic landscapes associated with underlying gene regulatory networks (GRNs). In this view, different phenotypes are associated with alternative states of complex nonlinear systems: stable attractors in deterministic models or modes of stationary distributions in stochastic descriptions. We provide theoretical and practical characterizations of these landscapes, specifically focusing on stochastic Slow Promoter Kinetics (SPK), a time scale relevant when transcription factor binding and unbinding are affected by epigenetic processes like DNA methylation and chromatin remodeling. In this case, largely unexplored except for numerical simulations, adiabatic approximations of promoter kinetics are not appropriate. In contrast to the existing literature, we provide rigorous analytic characterizations of multiple modes. A general formal approach gives insight into the influence of parameters and the prediction of how changes in GRN wiring, for example through mutations or artificial interventions, impact the possible number, location, and likelihood of alternative states. We adapt tools from the mathematical field of singular perturbation theory to represent stationary distributions of Chemical Master Equations for GRNs as mixtures of Poisson distributions and obtain explicit formulas for the locations and probabilities of metastable states as a function of the parameters describing the system. As illustrations, the theory is used to tease out the role of cooperative binding in stochastic models in comparison to deterministic models, and applications are given to various model systems, such as toggle switches in isolation or in communicating populations, a synthetic oscillator, and a trans-differentiation network.

| S-EPMC6396950 | biostudies-literature

Stochastic 16-state model of voltage gating of gap-junction channels enclosing fast and slow gates.

Project description:Gap-junction (GJ) channels formed of connexin (Cx) proteins provide a direct pathway for electrical and metabolic cell-cell interaction. Each hemichannel in the GJ channel contains fast and slow gates that are sensitive to transjunctional voltage (Vj). We developed a stochastic 16-state model (S16SM) that details the operation of two fast and two slow gates in series to describe the gating properties of homotypic and heterotypic GJ channels. The operation of each gate depends on the fraction of Vj that falls across the gate (VG), which varies depending on the states of three other gates in series, as well as on parameters of the fast and slow gates characterizing 1), the steepness of each gate's open probability on VG; 2), the voltage at which the open probability of each gate equals 0.5; 3), the gating polarity; and 4), the unitary conductances of the gates and their rectification depending on VG. S16SM allows for the simulation of junctional current dynamics and the dependence of steady-state junctional conductance (gj,ss) on Vj. We combined global coordinate optimization algorithms with S16SM to evaluate the gating parameters of fast and slow gates from experimentally measured gj,ss-Vj dependencies in cells expressing different Cx isoforms and forming homotypic and/or heterotypic GJ channels.

| S-EPMC3368129 | biostudies-literature

Force and kinetics of fast and slow muscle myosin determined with a synthetic sarcomere–like nanomachine

Project description: Not available

| S-EPMC10960843 | biostudies-literature

Split-belt treadmill adaptation shows different functional networks for fast and slow human walking.

Project description:New walking patterns can be learned over short time scales (i.e., adapted in minutes) using a split-belt treadmill that controls the speed of each leg independently. This leads to storage of a modified motor pattern that is expressed as an aftereffect in regular walking conditions and must be de-adapted to return to normal. Here we asked whether the nervous system adapts a general walking pattern that is used across many speeds or a specific pattern affecting only the two speeds experienced during split-belt training. In experiment 1, we tested three groups of healthy adult subjects walking at different split-belt speed combinations and then assessed aftereffects at a range of speeds. We found that aftereffects were largest at the slower speed that was used in split-belt training in all three groups, and it decayed gradually for all other speeds. Thus adaptation appeared to be more strongly linked to the slow walking speed. This result suggests a separation in the functional networks used for fast and slow walking. We tested this in experiment 2 by adapting walking to split belts and then determining how much fast regular walking washed out the slow aftereffect and vice versa. We found that 23-38% of the aftereffect remained regardless of which speed was washed out first. This demonstrates that there is only partial overlap in the functional networks coordinating different walking speeds. Taken together, our results suggest that there are some neural networks for controlling locomotion that are recruited specifically for fast versus slow walking in humans, similar to recent findings in other vertebrates.

| S-EPMC2807217 | biostudies-literature

Networks underlying paroxysmal fast activity and slow spike and wave in Lennox-Gastaut syndrome.

Project description:ObjectiveTo use EEG-fMRI to determine which structures are critically involved in the generation of paroxysmal fast activity (PFA) and slow spike and wave (SSW) (1.5-2.5 Hz), the characteristic interictal discharges of Lennox-Gastaut syndrome (LGS).MethodsWe studied 13 well-characterized patients with LGS using structural imaging and EEG-fMRI at 3 tesla. Ten patients had cortical structural abnormalities. PFA and SSW were considered as separate events in the fMRI analysis.ResultsSimultaneous with fMRI, PFA was recorded in 6 patients and SSW in 9 (in 2, both were recorded). PFA events showed almost uniform increases in blood oxygen level-dependent (BOLD) signal in "association" cortical areas, as well as brainstem, basal ganglia, and thalamus. SSW showed a different pattern of BOLD signal change with many areas of decreased BOLD signal, mostly in primary cortical areas. Two patients with prior callosotomy had lateralized as well as generalized PFA. The lateralized PFA was associated with a hemispheric version of the PFA pattern we report here.ConclusionPFA is associated with activity in a diffuse network that includes association cortices as well as an unusual pattern of simultaneous activation of subcortical structures (brainstem, thalamus, and basal ganglia). By comparison, the SSW pattern is quite different, with cortical and subcortical activations and deactivations. Regardless of etiology, it appears that 2 key, but distinct, patterns of diffuse brain network involvement contribute to the defining electrophysiologic features of LGS.

| S-EPMC3775693 | biostudies-literature

Stochastic Kinetics of Nascent RNA.

Project description:The stochastic kinetics of transcription is typically inferred from the distribution of RNA numbers in individual cells. However, cellular RNA reflects additional processes downstream of transcription, hampering this analysis. In contrast, nascent (actively transcribed) RNA closely reflects the kinetics of transcription. We present a theoretical model for the stochastic kinetics of nascent RNA, which we solve to obtain the probability distribution of nascent RNA per gene. The model allows us to evaluate the kinetic parameters of transcription from single-cell measurements of nascent RNA. The model also predicts surprising discontinuities in the distribution of nascent RNA, a feature which we verify experimentally.

| S-EPMC5033037 | biostudies-literature

Demography: Fast and Slow.

Project description:Scientific ideas on the human population tend to be rooted in a "slow demography" paradigm, which emphasizes an inertial, predictable, self-contained view of population dynamics, mostly dependent on fertility and mortality. Yet, demography can also move fast. At the country level, it is crucial to empirically assess how fast demography moves by taking migratory movements into account, in addition to fertility and mortality. We discuss these ideas and present new estimates of the speed of population change, that is, country-level population turnover rates, as well as the share of turnover due to migration, for all countries in the world with available data between 1990 and 2020. Population turnover is inversely related to population size and development, and migratory movements tend to become important factors in shaping demography for both small and highly developed countries. Longitudinally, we analyze annual turnover data for Italy and Germany, documenting the changing speed of population change over time and its determinants. Accepting the "fast and slow" demography perspective has several implications for science and policy, which we discuss.

| S-EPMC9305154 | biostudies-literature

slow/fast muscle with or without amplification

Project description:Comparing the gene expression profiles of slow and fast skeletal muscle (soleus VS FDB) with either amplified RNA (cRNA probes) or original mRNA (cDNA probes). The fidelity of mRNA amplification method in identifying the gene expression profiles of our samples were validated. Keywords: cell type comparison

2007-01-18 | GSE6654 | GEO

Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance.

Project description:Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha-gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions.

| S-EPMC5070951 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data