TICL – a web tool for network-based interpretation of compound lists inferred by high-throughput metabolomics

TICL – a web tool for network-based interpretation of compound lists

Tác giả: Alexey V. Antonov, Sabine Dietmann, Philip Wong, Hans W. Mewes

Lĩnh vực: Bioinformatics, Systems Biology, Genome-Oriented Bioinformatics

Nội dung tài liệu:

This article introduces TICL, a web-based tool designed for the interpretation of compound lists derived from high-throughput metabolomics studies. The rapidly advancing field of metabolomics generates extensive data, creating a challenge for understanding underlying biological mechanisms. While tools exist for analyzing gene and protein lists, there is a need for methods to interpret lists of differentially present compounds. TICL addresses this gap by providing a network-based analytical framework. It reconstructs probable metabolic transformation routes that connect compounds within a given list, leveraging the KEGG REACTION database. A key feature of TICL is its robust statistical framework, which employs Monte Carlo simulations to estimate the significance of the inferred network models through P-values. This allows for a quantitative assessment of the relationships between identified compounds, providing biologically meaningful insights into metabolic variations under different physiological conditions. The tool is freely accessible, offering a valuable resource for researchers in metabolomics and related fields.

Mục lục chi tiết:

• Introduction
• Results
• Materials and methods
• Global compound network
• Network inference procedure
• Statistical treatment
• References
• Discussion