Welcome to Deep-LASI’s documentation!

Deep-LASI (/dēp’lā-zē/) is a MATLAB program using Python libraries for automatized, multi-color single-molecule intensity trajectory analysis.

Deep-LASI – Deep-Learning Assisted Single-molecule Imaging analysis provides a tool for image processing and automated, unbiased analysis of single-molecule data. Deep-LASI comprises a collection of methods to characterize single molecule data with up to 3 channels in an automated fashion. The algorithms provided are routinely used to analyze data arising from multi-color single-molecule fluorescence experiments using TIRF or Confocal microscopy. Deep-LASI is based on the program TRacer, dedicated to finding single molecules, colocalizing molecules between different imaging channels, extracting their fluorescence signatures depending on the excitation and detection scheme and correcting the intensities for background signal depending on user-selected masks. The downstream analysis of single-molecule traces can be carried out manually as well as automatically using advanced deep-learning-assisted methods. Deep-LASI allows the determination of correction factors required for accurate FRET measurements and concomitantly distances between 2 or 3 fluorophores. Moreover, it identifies underlying conformational states and kinetics. Deep-LASI provides a complete architecture from reading the initial raw data to characterization and analysis, and display of the final analysis based on MATLAB and libraries using Python. Please cite the following papers if you use Deep-LASI in your own work, so we can continue development and support:

S Wanninger, P Asadiatouei, J Bohlen, CB Salem, P Tinnefeld, E Ploetzº and DC Lambº.
Deep-Learning Assisted, Single-molecule Imaging analysis (Deep-LASI) of multi-color
DNA Origami structures. (2023) DOI: https://doi.org/10.1101/2023.01.31.526220

Deep-LASI pulls data from the Repository and offers a simple and intuitive application programing interface (API).

To get started with Deep-LASI, please take a look at the Installation guide and How to get started section. Additional Example Galleries and reference material are provided in the Documentation section.

If you have any questions or problems, if you want to provide feedback about your experience with Deep-LASI or if you have any suggestions on how to further improve the program, please get in touch with us via the Forum or by Email.

Note

This project is under development.

Deep-LASI has its documentation hosted on Read the Docs.