Noise in biology

Tsimring, Lev S.

doi:10.1088/0034-4885/77/2/026601

Cited by 402 publications

(334 citation statements)

References 234 publications

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“…In recent years, it has been shown that random fluctuations can induce temporal and spatial behaviors that do not exist in the presence of purely deterministic dynamics (44,45). This novel perspective on the significance of randomness has become essential to the environmental sciences, where stochastic components are pervasive (45)(46)(47)(48). Even though noise-driven phenomena such as stochastic resonance, noise-controlled patterning, and noise-enhanced shift precursors have been recently identified in this context, unraveling how environmental fluctuations can cause structural changes in the dynamics is still a largely unexplored subject.…”

Section: Significancementioning

confidence: 99%

Stochastic ice stream dynamics

Mantelli

Bertagni

Ridolfi

2016

Proc. Natl. Acad. Sci. U.S.A.

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Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.

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Section: Significancementioning

confidence: 99%

Stochastic ice stream dynamics

Mantelli

Bertagni

Ridolfi

2016

Proc. Natl. Acad. Sci. U.S.A.

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“…Therefore, enhancement of cross-talk decreases variability between two kinases in a population. These results imply that cross-talk develops correlated fluctuations between kinases in a population, thereby assisting in the successful development of a robust adaptation machinery as observed in the bet-hedging program under diverse environmental conditions [22]. Here, an increase in the correlation between two different protein pool (with high Pearson's correlation coefficient) is observed for maximal cross-talk.…”

Section: Two Variable Mutual Informationmentioning

confidence: 71%

“…Inter-pathway cross-talk becomes prominent due to the limitation of common resources, defined as the overloaded condition. However, cross-talk effect becomes faint in the underloaded condition, where the level of available resources are present in sufficient amount [19,20,22,24,25]. A key source of survival strategy under diverse environmental conditions is the generation of fluctuations which induces non-genetic variability in a cellular population.…”

Section: Introductionmentioning

confidence: 99%

“…A key source of survival strategy under diverse environmental conditions is the generation of fluctuations which induces non-genetic variability in a cellular population. In such a situation, cells readjust to cope with the limited resources by introducing cross-correlation among a set of genes and thus implementing a successful bet-hedging program [22]. Cross-talk also facilitates synchronisation in different organs such as cardio-respiratory interaction, brain and tissues [23].…”

Section: Introductionmentioning

confidence: 99%

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Information Theoretical Study of Cross-Talk Mediated Signal Transduction in MAPK Pathways

Maity

Chaudhury

Banik

2017

Entropy

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Abstract:Biochemical networks having similar functional pathways are often correlated due to cross-talk among the homologous proteins in the different networks. Using a stochastic framework, we address the functional significance of the cross-talk between two pathways. A theoretical analysis on generic MAPK pathways reveals cross-talk is responsible for developing coordinated fluctuations between the pathways. The extent of correlation evaluated in terms of the information theoretic measure provides directionality to net information propagation. Stochastic time series suggest that the cross-talk generates synchronisation in a cell. In addition, the cross-interaction develops correlation between two different phosphorylated kinases expressed in each of the cells in a population of genetically identical cells. Depending on the number of inputs and outputs, we identify signal integration and signal bifurcation motif that arise due to inter-pathway connectivity in the composite network. Analysis using partial information decomposition, an extended formalism of multivariate information calculation, also quantifies the net synergy in the information propagation through the branched pathways. Under this formalism, signature of synergy or redundancy is observed due to the architectural difference in the branched pathways.

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“…However, we must be aware of the fact that our system is in-part discrete, which means that we rather seek trajectories to the basin of attraction in a cellular automaton as shown by Wuensche [12]. This factor of semi-discretion leads to the positive role of noise in biology [24], which we may briefly describe as a constant faltering of the system, which may more frequently occupy trajectory acquiring a broader part of the phase space.…”

Section: Resultsmentioning

confidence: 99%

Measurement in Biological Systems from the Self-organisation Point of View

Štys¹,

Urban²,

Rychtáriková³

et al. 2015

Bioinformatics and Biomedical Engineering

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Abstract. Measurement in biological systems became a subject of concern as a consequence of numerous reports on limited reproducibility of experimental results. To reveal origins of this inconsistency, we have examined general features of biological systems as dynamical systems far from not only their chemical equilibrium, but, in most cases, also of their Lyapunov stable states. Thus, in biological experiments, we do not observe states, but distinct trajectories followed by the examined organism. If one of the possible sequences is selected, a minute sub-section of the whole problem is obtained -sometimes in a seemingly highly reproducible manner. But the state of the organism is known only if a complete set of possible trajectories is known. And this is often practically impossible. Therefore, we propose a different framework for reporting and analysis of biological experiments, reflecting the view of non-linear mathematics. This view should be used to avoid overoptimistic results, which have to be consequently retracted or largely complemented. An increase of specification of experimental procedures is the way for better understanding of the scope of paths, which the biological system may be evolving. And it is hidden in the evolution of experimental protocols. Our system bioWes is a tool for objectivization of this knowledge.

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Noise in biology

Cited by 402 publications

References 234 publications

Stochastic ice stream dynamics

Stochastic ice stream dynamics

Information Theoretical Study of Cross-Talk Mediated Signal Transduction in MAPK Pathways

Measurement in Biological Systems from the Self-organisation Point of View

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