LINT-web

LINT-web performs lipidomic data processing and analysis to enable intra-omic integrative correlation-based prediction of lipid biological functions within high-dimensional lipidome datasets.

Key Features:

• Lipidomic data processing and analysis: Processes and analyzes high-dimensional lipidomic datasets.
• Intra-omic integrative correlation strategy: Implements an intra-omic integrative correlation strategy specifically tailored for lipidomic data mining.
• Genomic ontological correlation: Correlates genomic ontological results with lipid profiles using robust statistical methodologies.
• Database-independent analysis: Emphasizes intra-omic correlations rather than external database-dependent pathway analysis (e.g., KEGG, Reactome, HMDB).
• Prediction of lipid biological functions: Predicts potential biological functions of lipids based on intra-omic correlation patterns.
• Experimental validation: Has been validated using two distinct biological systems.

Scientific Applications:

• Lipid biological function prediction: Infers biological roles of individual lipids from lipidome data via correlation analyses.
• Lipidomic data mining: Facilitates discovery-driven mining of high-dimensional lipidomic datasets.
• Integrative omics correlation: Links lipidomic profiles to genomic ontological results to associate lipids with biological processes.
• Alternative pathway analysis: Serves as an alternative to pathway analyses relying on KEGG, Reactome, and HMDB by using intra-omic correlations.

Methodology:

Applies an intra-omic integrative correlation strategy and correlates lipidomic profiles with genomic ontological results using robust statistical methodologies.