Deep Learning-Assisted Analysis of Non-Equilibrium smFRET Trajectories under Low-SNR Conditions

Not scheduled
20m

Description

Single-molecule fluorescence resonance energy transfer (smFRET) is one of the
key techniques for resolving conformational dynamics of biomolecules. Most
studies in this field have focused on the dynamic conformational changes of
biomolecules under a stable external environment. However, the response of
many biomolecules to external stimuli, such as illumination at specific
wavelengths, changes in ion concentration, or temperature variation, can drive
their conformational dynamics from one steady state to another, resulting in a
non-equilibrium transition.
Importantly, such non-equilibrium transitions do not necessarily occur
instantaneously at the moment of external stimulation. Our project aims to
analyze smFRET trajectories under external perturbations by discretizing or
denoising noisy raw trajectories and identifying the position of the non
equilibrium transition point.

Primary authors

晓曼 王 Prof. 砚文 谭 (复旦大学) Dr 龙 陈 (香港大学)

Presentation materials