FRETboard

FRETboard performs semi-supervised statistical model fitting and analysis of Förster resonance energy transfer (FRET) single-molecule optical signals to improve parameter estimation and state assignment for biomolecular dynamics studies.

Key Features:

• Semi-Supervised Model Fitting: Interactive, user-guided statistical model fitting that enables reproduction of ground truth FRET statistics in simulated single-molecule scenarios.
• Efficiency in Parameter Estimation: Efficient estimation of model parameters for complex datasets, including datasets with up to eleven states, reducing analysis time relative to manual classification.
• Extensibility and Adaptability: Architecture designed to allow extension to new models to accommodate evolving FRET measurement techniques and analytical methodologies.

Scientific Applications:

• Single-Molecule FRET Analysis: Analysis of optical signals from FRET experiments for accurate state assignment and parameter extraction.
• Biomolecular Dynamics: Characterization of multiple conformational states and transitions in biomolecular systems at the nanoscale.
• Simulation Benchmarking: Validation and benchmarking of analysis approaches by reproducing ground truth FRET statistics in simulated datasets.

Methodology:

Application of a semi-supervised model-fitting approach with interactive user guidance to statistical models, validated by reproducing ground truth FRET statistics in simulated single-molecule scenarios and supporting parameter estimation for datasets with up to eleven states.