ramanbiolib-ui 1.0.0rc4

UI for ramanbiolib. Biomolecules identification search using Raman spectra.

RamanBiolib UI:

A standalone UI for Biomolecule Identifiaction by means of Raman Spectroscopy using RamanBiolib

Getting started

Python package

Installation:

pip install ramanbiolib_ui

Run:

ramanbiolib_ui

Windows executable file

You can download the Windows executable (.exe file) from the Releases section of this repository:

1. Go to the Releases page.
2. Find the latest release (or the version you want).
3. Under the Assets section, click on the ramanbiolib-ui.exe file to download it.
4. Run the downloaded file to start the application.

Note: This executable file is self-signed, so Windows and/or antivirus software may flag it as potentially unsafe. However, the file is secure — it is simply a packaged version of this open-source code created using PyInstaller. If you have any concerns about running the executable, you can always install and run the Python version instead.

How to use this tool

Spectral Linear Kernel (SLK) similarity search

This uses the full spectra plot to rank the database components by its SLK similarity to the unknown specturm.

Parameters:

• Raman spectrum file: the unnknown spectrum file containing the wavenumbers and intensity.
• Window size: the value of the window (W) parameter in SLK.
• Top N table: the number of components to show in the result table.
• Top N plot: the number of components to show in the result plot.

The search results display the ranked table of the most similar biomolecules in the RamanBiolib database:

and the spectra comparison plot:

Peak matching search

This matching calculate the matching between the specturm extracted peak positions and each database component peak positions.

Parameters:

• Source:
  • spectrum: the source is a spectrum file (as in SLK similarity search)
    • Raman spectrum file: the unnknown spectrum file containing the wavenumbers and intensity.
    • Peak detection prominence: the min prominence threshold for peak detection of the uploaded spectrum once the specturm is min-max normalized. The peak detection is done using scipy find_peaks function.
  • peaks list:
    • Peaks wavenumbers: the source is a comma-separated list of peaks wavenumbers positions (cm⁻¹). Example: 100,500,652,1205,1652 (step=1cm⁻¹, min=450, max=1800)
• Tolerance size: the simmetrical maximum distance tolerance for peak matching.
• Penalty type: the penalty function for PIUR calculation. Linear or Inverse power (1/x).
• Sorted by: the metric used to sort the results (IUR, MR, RMR, PIUR). Default IUR.
  • Considering query spectrum peaks Pa and DB spectrum peaks Pb:
    • MR (Matching Ratio) = intersection(Pa, Pb)/len(Pa)
    • RMR (Reverse Matching Ratio) = intersection(Pa, Pb)/len(Pb)
    • IUR (Intersection Union Ratio) = intersection(Pa, Pb)/union(Pa, Pb)
    • PIUR (Penalized Intersection Union Ratio) = penalized_intersection(Pa, Pb)/union(Pa, Pb)
• Top N table: the number of components to show in the result table.
• Top N plot: the number of components to show in the result plot.

The search results display the ranked table of the most similar biomolecules in the RamanBiolib database:

and the spectra comparison plot:

How to cite this tool

If you use this tool for research, please cite us:

Terán, M and Ruiz, JJ and Loza-Álvarez, P and Masip, D and Merino, D, Open Raman Spectral Library for Biomolecule Identification. Available at SSRN: https://ssrn.com/abstract=5185686 or http://dx.doi.org/10.2139/ssrn.5185686

License

GNU GPL v3