Bayesian inference of accurate population sizes and FRET efficiencies from single diffusing biomolecules.

It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from single-molecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in solution. Experimental methods of increasing cost and complexity are being developed to improve the accuracy and precision of data collection. However, the analysis of smFRET data sets currently relies on simplistic, and often arbitrary methods, for the selection and denoising of fluorescent bursts. Although these methods are satisfactory for the analysis of simple, low-noise systems with intermediate FRET efficiencies, they display systematic inaccuracies when applied to more complex systems. We have developed an inference method for the analysis of smFRET data from solution studies based on rigorous model-based Bayesian techniques. We implement a Monte Carlo Markov chain (MCMC) based algorithm that simultaneously estimates population sizes and intramolecular distance information directly from a raw smFRET data set, with no intermediate event selection and denoising steps. Here, we present both our parametric model of the smFRET process and the algorithm developed for data analysis. We test the algorithm using a combination of simulated data sets and data from dual-labeled DNA molecules. We demonstrate that our model-based method systematically outperforms threshold-based techniques in accurately inferring both population sizes and intramolecular distances.This is the final published version. It's also available from ACS in Analytical Chemistry: http://pubs.acs.org/doi/pdf/10.1021/ac501188r

The tetraspanin CD9 controls migration and proliferation of parietal epithelial cells and glomerular disease progression

International audienc

Product‐level estimates of exchange rate pass‐through: Evidence from Turkey*☆

We estimate the export and import pass-through rates using product-level data from Turkey. We find that the Turkish lira (TRY) exchange rate changes are mostly passed on to TRY prices of exports and imports—and, therefore, modestly to their prices in trading partners' currencies. The rate of average pass-through to TRY prices is estimated at 89% for imported goods and 82% for exported goods, with no apparent lags in the impact. Pass-through estimates by sector show variation and are relatively low for food and agricultural products. We argue that the fine-grained product-level data enable us to estimate the pass-through rates with better reliability and precision than we could by using only aggregated time-series data. We also introduce a pooled equation to estimate the difference between the export and import pass-through rates—a potentially useful statistic—in a way that allows for statistical inference