Biology subjects

Roberts, E.

Publications and source records attributed to Roberts, E..

3 recordsLinked to original sources

bioRxiv2018

Automatic error control during forward flux sampling of rare events in master equation models

Enhanced sampling methods, such as forward flux sampling (FFS), have great capacity for accelerating stochastic simulations of nonequilibrium biochemical systems involving rare events. However, the description of the tradeoffs between simulation efficiency and error in FFS remains incomplete. We present a novel and mathematically rigorous analysis of the errors in FFS that, for the first time, covers the contribution of every phase of the simulation. We derive a closed form expression for the optimally efficient count of samples to take in each FFS phase in terms of a fixed constraint on sampling error. We introduce a new method, forward flux pilot sampling (FFPilot), that is designed to take full advantage of our optimizing equation without prior information or assumptions about the phase weights and costs along the transition path. In simulations of both single- and multi-dimensional gene regulatory networks, FFPilot is able to completely control sampling error. Higher dimensional systems have additional sources of error and we show that this extra error can be traced to correlations between phases due to roughness on the probability landscape. Finally, we show that in sets of simulations with matched error, FFPilot is on the order of tens-to-hundreds of times faster than direct sampling, in a fashion that scales with the rarity of the events.

biophysics↗

bioRxiv2017

Neural network control of focal position during time-lapse microscopy of cells

Live-cell microscopy is quickly becoming an indispensable technique for studying the dynamics of cellular processes. Maintaining the specimen in focus during image acquisition is crucial for high-throughput applications, especially for long experiments or when a large sample is being continuously scanned. Automated focus control methods are often expensive, imperfect, or ill-adapted to a specific application and are a bottleneck for widespread adoption of high-throughput, live-cell imaging. Here, we demonstrate a neural network approach for automatically maintaining focus during bright-field microscopy. Z-stacks of yeast cells growing in a microfluidic device were collected and used to train a convolutional neural network to classify images according to their z-position. We studied the effect on prediction accuracy of the various hyperparameters of the neural network, including downsampling, batch size, and z-bin resolution. The network was able to predict the z-position of an image with {+/-}1 m accuracy, outperforming human annotators. Finally, we used our neural network to control microscope focus in real-time during a 24 hour growth experiment. The method robustly maintained the correct focal position compensating for 40 m of focal drift and was insensitive to changes in the field of view. Only ~100 annotated z-stacks were required to train the network making our method quite practical for custom autofocus applications.

cell biology↗

bioRxiv2017

Natural variation in stochastic photoreceptor specification and color preference in Drosophila

Each individual perceives the world in a unique way, but little is known about the genetic basis of variation in sensory perception. Here we investigated natural variation in the development and function of the color vision system of Drosophila. In the fly eye, the random mosaic of color-detecting R7 photoreceptor subtypes is determined by stochastic expression of the transcription factor Spineless (Ss). Individual R7s randomly choose between SsON or SsOFF fates at a ratio of 65:35, resulting in unique patterns but consistent proportions of cell types across genetically identical retinas. In a genome wide association study, we identified a naturally occurring insertion in a regulatory DNA element in the ss gene that lowers the ratio of SsON to SsOFF cells. This change in photoreceptor fates shifts the innate color preference of flies from green to blue. The genetic variant increases the binding affinity for Klumpfuss (Klu), a zinc finger transcriptional repressor that regulates ss expression. Klu is expressed at intermediate levels to determine the normal ratio of SsON to SsOFF cells. Thus, binding site affinity and transcription factor levels are finely tuned to regulate stochastic on/off gene expression, setting the ratio of alternative cell fates and ultimately determining color preference.

developmental biology↗