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Provides a methodology for fitting footprinting data using a likelihood-based approach.


This analysis tool will allow researchers to analyze their entire footprinting dataset, without filtering out noisy lanes and residues, or heuristic normalization, by employing a likelihood-based model fitting approach. This methodology allows for the rigorous estimation of parameters and parameter confidence intervals, to fit footprinting data to real physical models.

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