Proteomics Bioinformatic Analysis Service

With ongoing advancements in proteomics mass spectrometry technology, there has been a notable increase in the precision of analytical instruments, resulting in a richer dataset. While this detailed protein data is invaluable for deeper scientific investigation, the vast volumes of data produced by high-throughput proteomic screenings introduce substantial challenges in analyzing protein sample characteristics. Due to the complexity of handling such extensive mass spectrometry data manually, it is imperative to apply advanced bioinformatics techniques for effective analysis. MtoZ Biolabs boasts a team of bioinformatics analysts who excel in the extraction of insights from proteomics data, particularly focusing on the analysis of biological pathways and networks to swiftly identify extensive protein interactions. Leveraging advancements in bioinformatics analytical methods, we have developed a comprehensive platform for proteomics data analysis. Our suite of bioinformatics solutions encompasses quality assessment of omics data, differential expression analysis, annotation and enrichment analysis through GO, KEGG, and COG, as well as protein clustering and the analysis of interaction networks and pathways at multiple levels. Furthermore, we offer tailored bioinformatics services based on client specifications and scholarly references, enabling the extraction of valuable biological insights from high-throughput experimental data. This support aids our clients in areas such as drug development, toxicity testing, and the identification of disease markers.

 

Services at MtoZ Biolabs

1. Proteomic Data Quality

2. Differential Protein Statistical Analysis

3. GO Functional Annotation and Enrichment Analysis

4. KEGG Pathway and Enrichment Analysis

5. COG Functional Annotation and Enrichment Analysis

6. Differentially Expressed Proteins Custer Analysis

7. Protein Interaction Analysis

• • Differential Protein Analysis Service

  Differential protein analysis can significantly enhance the discovery of new biomarkers, improving the accuracy of biomarker identification and providing valuable insights for clinical disease analysis. MtoZ Biolabs offers precise differential protein analysis based on statistical data, identifying significant differences in protein levels under various physiological conditions and tissues. In the statistical analysis of differentially expressed proteins, FC ≥ 1.3 (or ≤ 1/1.3) is used as the threshold.

• • GO Functional Annotation and Enrichment Analysis Service

  The Gene Ontology (GO) is a database created by the Gene Ontology Consortium to provide a standardized vocabulary for gene and protein functions across species, which evolves with ongoing research. It uses a dynamic controlled vocabulary to describe the roles of genes and proteins within cells, offering a comprehensive description of gene and gene product attributes.

• • Differential Proteins Clustering Analysis Service

  To validate the selection of differentially expressed proteins or characteristic differentially expressed proteins, cluster analysis can be performed to group proteins based on expression trends, facilitating more intuitive proteomic data analysis. Services at MtoZ Biolabs 1. Hierarchical Cluster Analysis 2. K-means Cluster Analysis

• • COG Functional Annotation Analysis Service

  The COG (Clusters of Orthologous Groups) database is an early and widely used resource for the homologous classification of gene products, based on extensive comparisons of protein sequences from various organisms.

• • Protein Interaction Network Analysis Service

  STRING is a database that records predicted and experimentally validated protein-protein interactions (PPIs) across multiple species, including direct physical interactions and indirect functional associations. By integrating the results of differential expression analysis and the interaction pairs recorded in the database, a differential expression protein interaction network is constructed. During the analysis, differentially expressed proteins are mapped to the STRING database to obtain information......

• • Proteomics Data Quality Assessment Service

  Proteomics mass spectrometry data is fundamental to proteomics analysis. The quality of the mass spectra is closely related to the accuracy of the retrieval and analysis results. Therefore, the quality assessment of proteomics data is particularly important. To ensure the reliability of bioinformatics analysis, MtoZ Biolabs evaluates the identified proteomic data from the following four aspects:

• • KEGG Pathway Annotation and Enrichment Analysis Service

  KEGG (Kyoto Encyclopedia of Genes and Genomes) database is a database used for systematic analysis of metabolic pathways and functions of gene products in cells. KEGG helps to study genes and its expression information as a whole network. KEGG integrates data from genomes, chemical molecules, and biochemical systems, including metabolic pathways (PATHWAY), drugs (DRUG), diseases (DISEASE), gene sequences (GENES), and genomes (GENOME).