Integrated multi-omics analysis is a core paradigm in modern systems biology research. This service focuses on the integrated analysis of the proteome (including post-translational modification profiles) and the lipidome. It aims to break through the limitations of single-omics studies by systematically integrating data from different molecular layers, providing a panoramic view of the complete regulatory cascade from genetic code to metabolic phenotype.
Our analysis is based on a core biological principle: the synthesis, conversion, and degradation of metabolites within an organism are precisely controlled, directly or indirectly, by specific enzyme proteins (whose activity is often regulated by modifications such as phosphorylation) and upstream gene expression. By utilizing pathway databases like KEGG and combining cross-omics expression correlation analysis, this service enables:
We offer a one-stop solution from basic omics data generation to in-depth integrated analysis. Our specific services are detailed below:
| Analysis Type | Specific Service Items | Core Analysis Points |
| Proteomics Analysis | Global Qualitative and Quantitative Proteome Analysis | Protein identification, expression quantification, differential protein analysis, functional (GO) and pathway (KEGG) enrichment analysis. |
| Modification Proteomics Analysis | Post-Translational Modification Profile Analysis | Focuses on key modifications such as phosphorylation, acetylation, ubiquitination; modification site localization and quantification; differential modified protein and pathway analysis. |
| Lipidomics Analysis | Global Lipid Molecule Analysis | Qualitative and quantitative analysis of multiple lipid classes (e.g., glycerides, phospholipids, sphingolipids); differential lipid screening; lipid metabolic pathway change analysis. |
| Core Integrated Analysis | Cross-Omics Integration and Correlation Analysis | 1.Pathway Integration Analysis: Maps differential proteins/modified proteins and differential lipids onto KEGG pathways to reveal co-enriched regulatory and metabolic modules. 2.Correlation Network Analysis: Calculates expression correlation between proteins (modification levels) and lipid molecules, constructs regulatory networks, and screens for key driver nodes and potential novel relationships. |
The core advantage of this service lies in providing a systems biology perspective from "cause" (protein expression and modification) to "effect" (lipid metabolism), achieving efficient integration and deep correlation of multidimensional data through professional bioinformatics pipelines. We place particular emphasis on protein modification—a key link in functional regulation—revealing how it drives lipid network remodeling to gain mechanistic insights beyond single-omics studies. Furthermore, we offer flexible, personalized analysis plans for customized in-depth exploration based on your specific scientific questions.
Clarify the scientific question, determine experimental groups, sample size, and technical replication plan.
Separate extraction of proteins (and modifications) and lipids, enrichment (for modification analysis), and quality control testing.
Use high-resolution mass spectrometers for separate proteome/modification proteome and lipidome detection.
Provide a complete analysis report with charts and graphs, accompanied by expert biological interpretation of key findings and suggestions for follow-up research.