Biomedical subjects

G Grinstein

Publications and source records attributed to G Grinstein.

At least 19 recordsLinked to original sources

PubMed2006

Biased diffusion and universality in model queues.

We study the structure and robustness of universality classes for queueing, deriving analytic results for priority-based models with continuous-valued priorities. By mapping one model onto the problem of biased diffusion, we show that its distribution of waiting times, P(tau), decreases for large times tau as P(tau) approximately tau;{-3/2} or as P(tau) approximately tau;{-5/2}exp(-tau/tau_{0}) in different parameter regimes. In a second model, introducing a cost for switching between different classes of tasks substantially changes the asymptotic behavior of P(tau).

Journal Article↗

PubMed2006

Relationship between gene expression and observed intensities in DNA microarrays--a modeling study.

A theoretical study of the physical properties which determine the variation in signal strength from probe to probe on a microarray is presented. A model which incorporates probe-target hybridization, as well as the subsequent dissociation which occurs during stringent washing of the microarray, is introduced and shown to reasonably describe publicly available spike-in experiments carried out at Affymetrix. In particular, this model suggests that probe-target dissociation during the stringent wash plays a critical role in determining the observed hybridization intensities. In addition, it is demonstrated that non-specific hybridization introduces uncertainties which significantly limit the ability of any model to accurately quantify absolute gene expression levels while, in contrast, target folding appears to have little effect on these results. Finally, for data from target spike-in experiments, our model is shown to compare favorably with an existing statistical model in determining target concentration levels.

Gene Expression↗

PubMed2005

Escape or switching at short times.

In the standard Arrhenius picture [S. Arrhenius, Z. Phys. Chem., Stoechiom. Verwandtschaftsl. 4, 226 (1889); L. Néel, Ann. Geophys. (C.N.R.S.) 5, 99 (1949)] of thermal switching or escape from a metastable to a stable state, the escape probability per unit time P(s)(t) decreases monotonically with time t as P(s)(t) approximately e(-t/tau(D)), where the decay time tau(D) = tau0e(U/k(B)T), with U the energy barrier, k(B)T the thermal energy, and tau0 the time between escape attempts. Here, we extend the Arrhenius picture to shorter times by deriving general conditions under which P(s)(t) is peaked rather than monotonic, and showing that in the simplest scenario the peak time tau(P) diverges with tau(D) as ln(tau(D)).

Journal Article↗

PubMed2005

How white noise generates power-law switching in bacterial flagellar motors.

The clockwise (CW) or counterclockwise (CCW) spinning of a bacterial flagellar motor is controlled by the concentration [Y] of a phosphorylated protein, CheY-P. Representing the stochastic switching behavior of the motor by a dynamical two-state (CW and CCW) model, whose energy levels fluctuate in time (t) as [Y](t) fluctuates, we show that temporal fluctuations in [Y](t) can generate a power-law distribution for the durations of the CCW states, in agreement with recent experiments. Correlations between the duration times of nearby CCW (CW) intervals are predicted by our model, and shown to exist in the experimental data and to affect the power spectrum for motor switching.

Bacterial Proteins↗

PubMed2003

Modeling of DNA microarray data by using physical properties of hybridization.

A method of analyzing DNA microarray data based on the physical modeling of hybridization is presented. We demonstrate, in experimental data, a correlation between observed hybridization intensity and calculated free energy of hybridization. Then, combining hybridization rate equations, calculated free energies of hybridization, and microarray data for known target concentrations, we construct an algorithm to compute transcript concentration levels from microarray data. We also develop a method for eliminating outlying data points identified by our algorithm. We test the efficacy of these methods by comparing our results with an existing statistical algorithm, as well as by performing a cross-validation test on our model.

Algorithms↗

PubMed2003

Coarse graining in micromagnetics.

Numerical solutions of the micromagnetic Landau-Lifshitz-Gilbert equations provide valuable information at low temperatures (T), but produce egregious errors at higher T. For example, Curie temperatures are often overestimated by an order of magnitude. We show that these errors result from the use of block or coarse-grained variables, without a concomitant renormalization of the system parameters to account for the block size. Renormalization solves the problem of the Curie-point anomaly and improves the accuracy of more complicated micromagnetic simulations, even at low T.

Journal Article↗

PubMed2000

Low-frequency magnetic noise in micron-scale magnetic tunnel junctions.

We have observed low-frequency noise due to quasiequilibrium thermal magnetization fluctuations in micron-scale magnetic tunnel junctions (MTJs). This strongly field-dependent magnetic noise occurs within the magnetic hysteresis loops, either as 1/f or Lorentzian (random telegraph) noise. We attribute it to the thermally excited hopping of magnetic domain walls between pinning sites. Our results show that magnetic stability is a crucial factor in reducing the low-frequency noise in small MTJs.

Journal Article↗

PubMed2000

Thermally assisted magnetization reversal in submicron-sized magnetic thin films

We have measured the rate of thermally assisted magnetization reversal of submicron-sized magnetic thin films. For fields H just less than the zero-temperature switching field H(C), the probability of reversal, P(exp)(s)(t), increases for short times t, achieves a maximum value, and then decreases exponentially. Micromagnetic simulations exhibit the same behavior and show that the reversal proceeds through the annihilation of two domain walls that move from opposite sides of the sample. The behavior of P(exp)(s)(t) can be understood through a simple "energy-ladder" model of thermal activation.

Journal Article↗

PubMed1996