Kromath develops PARADISe, a software solution that utilizes tensor decomposition for optimized untargeted profiling analysis of Gas Chromatography Mass Spectrometry (GC-MS) data, enabling the identification and quantification of co-eluted compounds. By automating data processing, PARADISe significantly reduces analysis time from days to hours, making it suitable for both academic and industrial applications across various fields.
Funding
Funding not disclosed
Founders
Product
Problem
Analyzing Gas Chromatography Mass Spectrometry (GC-MS) data to identify and quantify compounds, especially when they co-elute, is traditionally time-consuming and subject to user variability. Existing methods often miss minor compounds, even when the raw data contains comprehensive information.
Solution
Kromath's PARADISe is a software solution designed to streamline and optimize untargeted profiling analysis of GC-MS data. By employing tensor decomposition, PARADISe resolves co-eluted compounds, improving their identification and quantification. The software automates data processing, significantly reducing analysis time and minimizing user dependence. PARADISe handles large, complex datasets, extracting maximum analytical information from raw signals, even quantifying compounds below the limit of detection. The final output is a peak table with estimated relative concentrations and mass spectra for each identified compound.
Target Audience
PARADISe is designed for researchers and professionals in academic and industrial settings who analyze GC-MS data for compound identification and quantification.
Features
- Deconvolutes and identifies co-eluted compounds using tensor decomposition (PARAFAC2).
- Automates pre-alignment of raw signals.
- Quantifies compounds even below the limit of detection.
- Processes large and complex datasets with consistent user interaction, regardless of sample size.
- Provides a user-friendly graphical interface for simplified operation.
- Offers a Professional Edition with automatic model fitting and evaluation, deep learning algorithm selection for peak finding, and batch analysis capabilities.
- Supports reading retention indices and automatic lookup of mass spectra in the NIST database (requires standalone NIST MSSearch).