Fig. 4: DLRN analysis of 2D time-resolved agarose gel electrophoresis and time resolved transient absorption.
From: Deep Learning Reaction Framework (DLRN) for kinetic modeling of time-resolved data
a Example of a synthetic agarose gel used for the kinetic model analysis with DLRN. b Expected model and DLRN analysis performed on the image shown in panel a. DLRN can correctly predict both the kinetic model and the time constant associated with each pathway. c Comparison between DLRN prediction (continuous lines) and expected (dashed lines) amplitude from the image in a. d Example of transient absorption signal used for the DLRN analysis. e Expected model and DLRN analysis performed on the image shown in panel d. DLRN predicts correctly the model and time constants within a small error. f Comparison between DLRN prediction continuous lines) and expected (dashed lines) amplitude from the image in d.
