RESUMEN
Calculations of entropy of a signal or mutual information between two variables are valuable analytical tools in the field of neuroscience. They can be applied to all types of data, capture non-linear interactions and are model independent. Yet the limited size and number of recordings one can collect in a series of experiments makes their calculation highly prone to sampling bias. Mathematical methods to overcome this so-called "sampling disaster" exist, but require significant expertise, great time and computational costs. As such, there is a need for a simple, unbiased and computationally efficient tool for estimating the level of entropy and mutual information. In this article, we propose that application of entropy-encoding compression algorithms widely used in text and image compression fulfill these requirements. By simply saving the signal in PNG picture format and measuring the size of the file on the hard drive, we can estimate entropy changes through different conditions. Furthermore, with some simple modifications of the PNG file, we can also estimate the evolution of mutual information between a stimulus and the observed responses through different conditions. We first demonstrate the applicability of this method using white-noise-like signals. Then, while this method can be used in all kind of experimental conditions, we provide examples of its application in patch-clamp recordings, detection of place cells and histological data. Although this method does not give an absolute value of entropy or mutual information, it is mathematically correct, and its simplicity and broad use make it a powerful tool for their estimation through experiments.
RESUMEN
Recent development of single-molecule techniques to study pre-mRNA splicing has provided insights into the dynamic nature of the spliceosome. Colocalization single-molecule spectroscopy (CoSMoS) allows following spliceosome assembly in real time at single-molecule resolution in the full complexity of cellular extracts. A detailed protocol of CoSMoS has been published previously (Anderson and Hoskins, Methods Mol Biol 1126:217-241, 2014). Here, we provide an update on the technical advances since the first CoSMoS studies including slide surface treatment, data processing, and representation. We describe various labeling strategies to generate RNA reporters with multiple dyes (or other moieties) at specific locations.