Quantitative Aspects of Single-Molecule Microscopy: Information-theoretic analysis of single-molecule data

Single-molecule microscopy is a relatively new optical microscopy technique that allows the detection of individual molecules such as proteins in a cellular context. This technique has generated significant interest among biologists, biophysicists, and biochemists, as it holds the promise to provide novel insights into subcellular processes and structures that otherwise cannot be gained through traditional experimental approaches. Single-molecule experiments place stringent demands on experimental and algorithmic tools due to the low signal levels and the presence of significant extraneous noise sources. Consequently, this has necessitated the use of advanced statistical signal- and image-processing techniques for the design and analysis of single-molecule experiments. In this tutorial article, we provide an overview of single-molecule microscopy from early works to current applications and challenges. Specific emphasis will be on the quantitative aspects of this imaging modality, in particular single-molecule localization and resolvability, which will be discussed from an information-theoretic perspective. We review the stochastic framework for image formation, different types of estimation techniques, and expressions for the Fisher information matrix. We also discuss several open problems in the field that demand highly nontrivial signal processing algorithms.