ECCO 2024
Abstract Submission

65. Algorithms supporting analysis of mass spectra of metabolites and lipids

Invited abstract in session TC-1: Algorithms, stream Algorithms.

Thursday, 11:30 - 13:00
Room: L226

Authors (first author is the speaker)

1. Marcin Borowski
Institute of Computing Science, Poznan University of Technology

Abstract

In recent years, advancements in mass spectrometry technology have led to a significant increase in the amount of data generated during the analysis of metabolites and lipids. However, analyzing these data can be challenging due to their complexity and diversity. To address this challenge, we have developed an advanced algorithm that can assist in the analysis of mass spectra associated with metabolomics and lipidomics.
The algorithm uses data acquired during mass spectrum analysis and reference databases to identify and determine the corresponding fragments of chemical compounds. Additionally, based on the properties of functional groups, the algorithm predicts possible bonds between the found compounds and constructs ready-made combinations. Researchers can customize the search area for potential compounds and functional groups using a configurable file, as the algorithm has a flexible design.
When we tested the algorithm on several mass spectra, we obtained promising results. Based on these results, we generated reports detailing the configuration file settings, corresponding mass spectrum compounds, and identification suggestions. These reports were analyzed and presented in the experimental section of the work, where we concluded the effectiveness of the algorithm and its potential applications in practical use.
The conclusions of our work confirm that the described algorithm can be a valuable tool in the analysis of mass spectra in metabolomics and lipidomics, contributing to a more efficient and accurate study of small-molecule chemical compounds in organisms. Given its flexibility and adaptability to different research needs, it can prove useful for a wide range of scientists and researchers in the field.

Keywords

Status: accepted

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