<br/>Single molecule measurements in real time provide unique information at the molecular and cellular level inaccessible from ensemble experiments. The trajectories recorded are intrinsically stochastic with a significant signal to noise ratio, and post-measurement analysis via statistical indicators is used to fit probabilistic models for further interpretation. In this work we will introduce the concept of information entropies into the analysis of single molecule measurements and show how these indicators provide detailed information about the mechanism, memory and complexity of the chemical process . During my talk, I will illustrate how information entropies can be utilized in real experiments by numerically studying representative hidden Markov chains. Our predictions are are contrasted with those obtained with other indicators, such as two-time correlation functions and the constrained mean dwell times. The conclusion of these investigations indicate that information entropies reveal equivalent information to multidimensional correlation functions with fewer data, can reconstruct complex kinetic schemes and provide a frequency-domain approach to single molecule studies.

Information entropies in single molecule studies

255th National Meeting (2018)

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