Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data

We address the problem of analyzing sets of noisy time-varying signals that all report on the same process but confound straightforward analyses due to complex inter-signal heterogeneities and measurement artifacts. In particular we consider single-molecule experiments which indirectly measure the distinct steps in a biomolecular process via observations of noisy time-dependent signals such as a fluorescence intensity or bead position. Straightforward hidden Markov model (HMM) analyses attempt to characterize such processes in terms of a set of conformational states, the transitions that can occur between these states, and the associated rates at which those transitions occur; but require ad-hoc post-processing steps to combine multiple signals. Here we develop a hierarchically coupled HMM that allows experimentalists to deal with inter-signal variability in a principled and automatic way. Our approach is a generalized expectation maximization hyperparameter point estimation procedure with variational Bayes at the level of individual time series that learns an single interpretable representation of the overall data generating process.Comment: 9 pages, 5 figure

A Variational Perspective on Generative Flow Networks

Generative flow networks (GFNs) are a class of probabilistic models for sequential sampling of composite objects, proportional to a target distribution that is defined in terms of an energy function or a reward. GFNs are typically trained using a flow matching or trajectory balance objective, which matches forward and backward transition models over trajectories. In this work we introduce a variational objective for training GFNs, which is a convex combination of the reverse- and forward KL divergences, and compare it to the trajectory balance objective when sampling from the forward- and backward model, respectively. We show that, in certain settings, variational inference for GFNs is equivalent to minimizing the trajectory balance objective, in the sense that both methods compute the same score-function gradient. This insight suggests that in these settings, control variates, which are commonly used to reduce the variance of score-function gradient estimates, can also be used with the trajectory balance objective. We evaluate our findings and the performance of the proposed variational objective numerically by comparing it to the trajectory balance objective on two synthetic tasks

Universal and wide shear zones in granular bulk flow

We present experiments on slow granular flows in a modified (split-bottomed) Couette geometry in which wide and tunable shear zones are created away from the sidewalls. For increasing layer heights, the zones grow wider (apparently without bound) and evolve towards the inner cylinder according to a simple, particle-independent scaling law. After rescaling, the velocity profiles across the zones fall onto a universal master curve given by an error function. We study the shear zones also inside the material as function of both their local height and the total layer height.Comment: Minor corrections, accepted for PRL (4 pages, 6 figures

Eccentric binary black holes: Comparing numerical relativity and small mass-ratio perturbation theory

The modelling of unequal mass binary black hole systems is of high importanceto detect and estimate parameters from these systems. Numerical relativity (NR)is well suited to study systems with comparable component masses, m_1\simm_2, whereas small mass ratio (SMR) perturbation theory applies to binarieswhere $q=m_2/m_1as a function of mass ratio for eccentric non-spinning binary black holes. Weproduce$52$NR simulations with mass ratios between$1:10$and$1:1$andinitial eccentricities up to$0.7$. From these we extract quantities likegravitational wave energy and angular momentum fluxes and periastron advance,and assess their accuracy. To facilitate comparison, we develop tools to mapbetween NR and SMR inspiral evolutions of eccentric binary black holes. Wederive post-Newtonian accurate relations between different definitions ofeccentricity. Based on these analyses, we introduce a new definition ofeccentricity based on the (2,2)-mode of the gravitational radiation, whichreduces to the Newtonian definition of eccentricity in the Newtonian limit.From the comparison between NR simulations and SMR results, we quantify theunknown next-to-leading order SMR contributions to the gravitational energy andangular momentum fluxes, and periastron advance. We show that in the comparablemass regime these contributions are subdominant and higher order SMRcontributions are negligible.<br

Multiple Lac-mediated loops revealed by Bayesian statistics and tethered particle motion

The bacterial transcription factor LacI loops DNA by binding to two separate locations on the DNA simultaneously. Despite being one of the best-studied model systems for transcriptional regulation, the number and conformations of loop structures accessible to LacI remain unclear, though the importance of multiple co-existing loops has been implicated in interactions between LacI and other cellular regulators of gene expression. To probe this issue, we have developed a new analysis method for tethered particle motion, a versatile and commonly-used in vitro single-molecule technique. Our method, vbTPM, performs variational Bayesian inference in hidden Markov models. It learns the number of distinct states (i.e., DNA-protein conformations) directly from tethered particle motion data with better resolution than existing methods, while easily correcting for common experimental artifacts. Studying short (roughly 100 bp) LacI-mediated loops, we provide evidence for three distinct loop structures, more than previously reported in single-molecule studies. Moreover, our results confirm that changes in LacI conformation and DNA binding topology both contribute to the repertoire of LacI-mediated loops formed in vitro, and provide qualitatively new input for models of looping and transcriptional regulation. We expect vbTPM to be broadly useful for probing complex protein-nucleic acid interactions.Comment: 34 pages, 25 figures, including Supporting information. To appear in Nucleic Acids Research. Accompanying open-source software: http://sourceforge.net/projects/vbtpm