FoCuS-point

FoCuS-point analyzes fluorescence correlation spectroscopy (FCS) data to quantify molecular mobility and interaction dynamics in STED-FCS experiments using time-correlated single-photon counting (TCSPC) and time-gated detection.

Key Features:

• TCSPC correlation algorithms: Implements time-correlated single-photon counting correlation algorithms for high-temporal-resolution analysis of fluorescence events.
• Time-gated filtering: Applies time-gated filtering to select specific photon arrival time windows and improve signal-to-noise in time-gated STED-FCS data.
• STED-FCS compatibility: Supports analysis of super-resolution STED microscopy combined with FCS, including experiments employing time-gated detection.
• Advanced fitting algorithms: Provides sophisticated fitting of correlation curves to extract diffusion coefficients and kinetic parameters.
• Batch data processing: Enables processing of multiple FCS data files for high-throughput analysis.
• Data visualization: Produces visual representations of correlation functions and fitted results for interpretation of molecular dynamics.
• Implementation: Implemented in Python.

Scientific Applications:

• Super-resolution diffusion measurements: Quantifies diffusion and mobility at the nanoscale in STED-FCS experiments.
• Protein interactions and kinetics: Extracts interaction dynamics and receptor–ligand binding kinetics from correlation and fitting analyses.
• Live-cell molecular dynamics: Measures molecular mobility and interaction dynamics within living cells using time-gated FCS approaches.

Methodology:

Uses time-correlated single-photon counting (TCSPC) correlation algorithms, time-gated filtering, correlation-curve fitting via advanced fitting algorithms, batch data processing, and data visualization.