Introduction

The lipidomics field faces unique challenges in standardizing its nomenclature and measurement precision, unlike genomics, transcriptomics, and proteomics, which have relatively consistent units of measurement (genes, transcripts, proteins). In lipidomics, measurement limitations frequently prevent analysts from identifying lipids at precise structural or isomeric subspecies levels. Consequently, lipid identification often relies on generalized representations, such as abstract class or species names aligned with established ontologies. This, along with variations in database standards, creates a particularly fragmented and complex landscape for prior knowledge in lipidomics.

LipiNet is designed to address these challenges by integrating information across disparate lipidomics databases, each with different identifiers and varying levels of lipid resolution. By unifying these resources and accounting for the inherent ambiguity in lipid identification, LipiNet enables more cohesive and comprehensive network analyses across lipidomics databases.

Core features

• Multi-layered network construction and analysis

• Cross-database lipid identifier integration

• Tools for filtering, analysing and visualising by layers