With the development of proteomics mass spectrometry analysis technology, the accuracy of proteomics analysis instruments continues to improve, and more valuable data are obtained to support research and development as a result. Although detailed protein data information facilitates more in-depth studies of proteomics, the massive protein sample data generated by high-throughput proteomics assays also poses considerable challenges for protein characterization. Nevertheless, it is extremely difficult to manually analyze protein features by processing the massive amount of mass spectrometry information. Data were needed to be analyzed and processed using specialized bioinformatics methods.
Our PhD-level bioinformatics analysis team specializes in knowledge mining of proteomics data, especially the analysis of biological pathways and networks, and rapid discovery of large amounts of protein interaction data. We have built an industry-leading data collection and analysis platform for proteomics discovery and target proteomics based on research advances in bioinformatics analysis methods.
The platform provides a complete set of bioinformatics solutions, including:
Standard Data Analysis Content | |
Mass spectrometry data analysis | Spectral peptide quality deviation distribution, peptide length distribution, unique peptide number distribution, protein coverage distribution |
Quantitative Protein Analysis | Protein abundance value distribution, protein abundance ratio distribution between samples, PCA analysis, statistical analysis of significant differences |
Protein Functional Analysis | Total protein and differential protein GO secondary classification, COG function classification, KEGG annotation, subcellular organelle location, domain annotation, signal peptide prediction and PPI prediction; differential protein GO, KEGG, domain enrichment analysis |
Advanced Data Analysis Content | |
Protein Gene Chromosome Localization | Obtain distribution of genes encoding proteins on chromosomes |
WGCNA Analysis | Predict functional clustering and network interactions by protein expression level; correlate with phenotype data to obtain key proteins or protein complexes that influence phenotype |
Trend Cluster Analysis | Obtain protein expression trend patterns |
Molecular Typing | Molecular typing for large cohort samples |
Survival Curve Analysis | Study the relationship between influencing factors and survival time and outcome |
ROC Curves | Evaluate predictive accuracy by combining specificity and sensitivity, such as biomarker impact assessment on tumor grade |
We can provide customized bioinformatics solutions for each contract research project based on the client's requirements and references to discover biological knowledge from high-throughput experimental data. We support clients with drug design, toxicity analysis and disease marker discovery.
Thanks to our biological expertise and data analysis capabilities, we have become a leader in the field of proteomics. We have more than ten years of experience in large-scale proteomic research. Through these proprietary project experiences, we have established a unique protein database and ensured that all collected proteomic data are optimized, standardized and formatted for further analysis.
In addition, through the analysis of tens of thousands of DIA samples, we have also formed an industry-leading understanding of the protein groups in different species and biological matrices.
All you need to do is send us a sample, tell us what you need, and we will provide you with the best service and results. No-obligation consultation is always welcome!
4D Proteomics with Data-Independent Acquisition (DIA)
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×Specializing in proteomics, Creative Proteomics offers cutting-edge protein analysis services. Our distinctive approach revolves around harnessing the power of DIA technology, enabling us to deliver precise and comprehensive insights that drive advancements in research and industry.