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Inference of DNA sequences from mechanical unzipping: an ideal-case study
V Baldazzi1, S Cocco, E Marinari
1Dipartimento di Fisica, Università di Roma Tor Vergata, Roma, Italy.
Abstract:
The performances of Bayesian inference to predict the sequence of DNA molecules from fixed-force unzipping experiments are investigated. We show that the probability of misprediction decreases exponentially with the amount of collected data. The decay rate is calculated as a function of biochemical parameters (binding free energies), the sequence content, the applied force, the elastic properties of a DNA single strand, and time resolution.
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