Bayesian Nonparametrics for FRET using Realistic Integrative Detectors
Saurabh, A.; Wisna, G. B. M.; Schweiger, M. C.; Hariadi, R. F.; Presse, S.
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Biomolecular dynamics are often strikingly heterogeneous, with individual molecules sampling different states and kinetics--violating the "average molecule" assumption. Yet FRET analyses cannot resolve such variability or distinguish states differing mainly in kinetics, rather than FRET efficiency, as molecular configurations are projected onto 1D FRET signals. Here we introduce BNP-FRET-Bin, inferring state numbers and their kinetics directly from FRET data. In doing so, we eliminate user-specified parameters and expose molecule-to-molecule heterogeneity revealing new biologically relevant Holliday junction states with near identical FRET efficiencies.
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