13,297 research outputs found
Crosstalk and the Dynamical Modularity of Feed-Forward Loops in Transcriptional Regulatory Networks
Network motifs, such as the feed-forward loop (FFL), introduce a range of complex behaviors to transcriptional regulatory networks, yet such properties are typically determined from their isolated study. We characterize the effects of crosstalk on FFL dynamics by modeling the cross regulation between two different FFLs and evaluate the extent to which these patterns occur in vivo. Analytical modeling suggests that crosstalk should overwhelmingly affect individual protein-expression dynamics. Counter to this expectation we find that entire FFLs are more likely than expected to resist the effects of crosstalk (approximate to 20% for one crosstalk interaction) and remain dynamically modular. The likelihood that cross-linked FFLs are dynamically correlated increases monotonically with additional crosstalk, but is independent of the specific regulation type or connectivity of the interactions. Just one additional regulatory interaction is sufficient to drive the FFL dynamics to a statistically different state. Despite the potential for modularity between sparsely connected network motifs, Escherichia coli (E. coli) appears to favor crosstalk wherein at least one of the cross-linked FFLs remains modular. A gene ontology analysis reveals that stress response processes are significantly overrepresented in the cross-linked motifs found within E. coli. Although the daunting complexity of biological networks affects the dynamical properties of individual network motifs, some resist and remain modular, seemingly insulated from extrinsic perturbations-an intriguing possibility for nature to consistently and reliably provide certain network functionalities wherever the need arise
Inverse velocity statistics in two dimensional turbulence
We present a numerical study of two-dimensional turbulent flows in the
enstrophy cascade regime, with different large-scale forcings and energy sinks.
In particular, we study the statistics of more-than-differentiable velocity
fluctuations by means of two recently introduced sets of statistical
estimators, namely {\it inverse statistics} and {\it second order differences}.
We show that the 2D turbulent velocity field, , cannot be simply
characterized by its spectrum behavior, . There
exists a whole set of exponents associated to the non-trivial smooth
fluctuations of the velocity field at all scales. We also present a numerical
investigation of the temporal properties of measured in different
spatial locations.Comment: 9 pages, 12 figure
Balancing noise and plasticity in eukaryotic gene expression
Coupling the control of expression stochasticity (noise) to the ability of
expression change (plasticity) can alter gene function and influence
adaptation. A number of factors, such as transcription re-initiation, strong
chromatin regulation or genome neighboring organization, underlie this
coupling. However, these factors do not necessarily combine in equivalent ways
and strengths in all genes. Can we identify then alternative architectures that
modulate in distinct ways the linkage of noise and plasticity? Here we first
show that strong chromatin regulation, commonly viewed as a source of coupling,
can lead to plasticity without noise. The nature of this regulation is relevant
too, with plastic but noiseless genes being subjected to general activators
whereas plastic and noisy genes experience more specific repression.
Contrarily, in genes exhibiting poor transcriptional control, it is
translational efficiency what separates noise from plasticity, a pattern
related to transcript length. This additionally implies that genome neighboring
organization -as modifier- appears only effective in highly plastic genes. In
this class, we confirm bidirectional promoters (bipromoters) as a configuration
capable to reduce coupling by abating noise but also reveal an important
trade-off, since bipromoters also decrease plasticity. This presents ultimately
a paradox between intergenic distances and modulation, with short intergenic
distances both associated and disassociated to noise at different plasticity
levels. Balancing the coupling among different types of expression variability
appears as a potential shaping force of genome regulation and organization.
This is reflected in the use of different control strategies at genes with
different sets of functional constraints
Statistical Physics of Vehicular Traffic and Some Related Systems
In the so-called "microscopic" models of vehicular traffic, attention is paid
explicitly to each individual vehicle each of which is represented by a
"particle"; the nature of the "interactions" among these particles is
determined by the way the vehicles influence each others' movement. Therefore,
vehicular traffic, modeled as a system of interacting "particles" driven far
from equilibrium, offers the possibility to study various fundamental aspects
of truly nonequilibrium systems which are of current interest in statistical
physics. Analytical as well as numerical techniques of statistical physics are
being used to study these models to understand rich variety of physical
phenomena exhibited by vehicular traffic. Some of these phenomena, observed in
vehicular traffic under different circumstances, include transitions from one
dynamical phase to another, criticality and self-organized criticality,
metastability and hysteresis, phase-segregation, etc. In this critical review,
written from the perspective of statistical physics, we explain the guiding
principles behind all the main theoretical approaches. But we present detailed
discussions on the results obtained mainly from the so-called
"particle-hopping" models, particularly emphasizing those which have been
formulated in recent years using the language of cellular automata.Comment: 170 pages, Latex, figures include
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