2,944 research outputs found
Slow nucleic acid unzipping kinetics from sequence-defined barriers
Recent experiments on unzipping of RNA helix-loop structures by force have
shown that about 40-base molecules can undergo kinetic transitions between two
well-defined `open' and `closed' states, on a timescale = 1 sec [Liphardt et
al., Science 297, 733-737 (2001)]. Using a simple dynamical model, we show that
these phenomena result from the slow kinetics of crossing large free energy
barriers which separate the open and closed conformations. The dependence of
barriers on sequence along the helix, and on the size of the loop(s) is
analyzed. Some DNAs and RNAs sequences that could show dynamics on different
time scales, or three(or more)-state unzipping, are proposed.Comment: 8 pages Revtex, including 4 figure
Adaptive Cluster Expansion for Inferring Boltzmann Machines with Noisy Data
We introduce a procedure to infer the interactions among a set of binary
variables, based on their sampled frequencies and pairwise correlations. The
algorithm builds the clusters of variables contributing most to the entropy of
the inferred Ising model, and rejects the small contributions due to the
sampling noise. Our procedure successfully recovers benchmark Ising models even
at criticality and in the low temperature phase, and is applied to
neurobiological data.Comment: Accepted for publication in Physical Review Letters (2011
Large Pseudo-Counts and -Norm Penalties Are Necessary for the Mean-Field Inference of Ising and Potts Models
Mean field (MF) approximation offers a simple, fast way to infer direct
interactions between elements in a network of correlated variables, a common,
computationally challenging problem with practical applications in fields
ranging from physics and biology to the social sciences. However, MF methods
achieve their best performance with strong regularization, well beyond Bayesian
expectations, an empirical fact that is poorly understood. In this work, we
study the influence of pseudo-count and -norm regularization schemes on
the quality of inferred Ising or Potts interaction networks from correlation
data within the MF approximation. We argue, based on the analysis of small
systems, that the optimal value of the regularization strength remains finite
even if the sampling noise tends to zero, in order to correct for systematic
biases introduced by the MF approximation. Our claim is corroborated by
extensive numerical studies of diverse model systems and by the analytical
study of the -component spin model, for large but finite . Additionally
we find that pseudo-count regularization is robust against sampling noise, and
often outperforms -norm regularization, particularly when the underlying
network of interactions is strongly heterogeneous. Much better performances are
generally obtained for the Ising model than for the Potts model, for which only
couplings incoming onto medium-frequency symbols are reliably inferred.Comment: 25 pages, 17 figure
Inferring DNA sequences from mechanical unzipping data: the large-bandwidth case
The complementary strands of DNA molecules can be separated when stretched
apart by a force; the unzipping signal is correlated to the base content of the
sequence but is affected by thermal and instrumental noise. We consider here
the ideal case where opening events are known to a very good time resolution
(very large bandwidth), and study how the sequence can be reconstructed from
the unzipping data. Our approach relies on the use of statistical Bayesian
inference and of Viterbi decoding algorithm. Performances are studied
numerically on Monte Carlo generated data, and analytically. We show how
multiple unzippings of the same molecule may be exploited to improve the
quality of the prediction, and calculate analytically the number of required
unzippings as a function of the bandwidth, the sequence content, the elasticity
parameters of the unzipped strands
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Different haemodynamic (24-h ambulatory blood-pressure monitoring) and rennin-inhibiting effect of a 1 week treatment with enalapril and lisinopril
Ambulatory blood pressure and heart rate monitoring were used for comparing the antihypertensive effect of a 1-week treatment with enalapril and lisinopril 10 mg once daily (double-blind crossover placebo-controlled d y ). Twelve outpatients with mild to moderate hypertension were treated. Both drugs had a significant and identical hypotensive effect. Neither drug affected the diurnal rhythm of blood pressure or heart rate. Therefore the two drugs are equipotent antihypertensive agents. Both drugs inhibited ACE activity to a highly significant extent, but in this regard lisinopril was more effective than enalapril. However, lisinopril's greater ACE inhibition was not accompanied by a greater hypotensive effect. The clinical value of this difference is not yet established
Unzipping Dynamics of Long DNAs
The two strands of the DNA double helix can be `unzipped' by application of
15 pN force. We analyze the dynamics of unzipping and rezipping, for the case
where the molecule ends are separated and re-approached at constant velocity.
For unzipping of 50 kilobase DNAs at less than about 1000 bases per second,
thermal equilibrium-based theory applies. However, for higher unzipping
velocities, rotational viscous drag creates a buildup of elastic torque to
levels above kBT in the dsDNA region, causing the unzipping force to be well
above or well below the equilibrium unzipping force during respectively
unzipping and rezipping, in accord with recent experimental results of Thomen
et al. [Phys. Rev. Lett. 88, 248102 (2002)]. Our analysis includes the effect
of sequence on unzipping and rezipping, and the transient delay in buildup of
the unzipping force due to the approach to the steady state.Comment: 15 pages Revtex file including 9 figure
Introduction to special section: Stress transfer, earthquake triggering, and time-dependent seismic hazard
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