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    Resources

      Proteomics Databases

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      Metabolomics Databases

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    • • Application of MRM/PRM in Proteomics

      In proteomic research, quantitative analysis is essential for understanding complex biochemical processes within biological systems. Multiple Reaction Monitoring (MRM) and Parallel Reaction Monitoring (PRM) are highly sensitive and specific mass spectrometry techniques widely employed in quantitative proteomics.

    • • Workflow of MRM/PRM Quantitative Analysis

      MRM (Multiple Reaction Monitoring) and PRM (Parallel Reaction Monitoring) are widely used quantitative analysis techniques in modern mass spectrometry, applied extensively in biomedical research, drug development, and clinical diagnostics. They enable quantitative analysis of specific target molecules with high sensitivity and selectivity, providing researchers with powerful analytical tools.

    • • Principle of MRM/PRM Quantitative Proteomics

      Quantitative proteomics is a critical component of modern biological research, primarily used to understand the functions of proteins within organisms, their interactions, and the changes they undergo in various diseases and physiological states. Multiple Reaction Monitoring (MRM) and Parallel Reaction Monitoring (PRM) are two essential quantitative analysis methods that efficiently and accurately detect and quantify proteins.

    • • Advantages and Disadvantages of MRM/PRM Techniques

      In the fields of biology and medicine, mass spectrometry (MS) technologies play a crucial role in proteomics, metabolomics, and various other domains. Multiple Reaction Monitoring (MRM) and Parallel Reaction Monitoring (PRM) are two commonly used mass spectrometry analysis techniques.

    • • Mechanism of Targeted Proteomics

      The core of targeted proteomics lies in the selective detection of specific proteins. Unlike global proteomics, targeted proteomics focuses only on known target proteins, typically based on prior biological research or clinical data. This approach often combines high-throughput mass spectrometry (MS) with specific antibodies, forming a "mass spectrometry-antibody" detection strategy.

    • • Application of Targeted Proteomics

      Targeted proteomics involves the precise measurement and analysis of predefined proteins in biological samples using specific methods, such as mass spectrometry. Compared to global proteomics, targeted proteomics emphasizes data accuracy and reproducibility. The process typically includes selecting target proteins, optimizing detection conditions, and validating results.

    • • Advantages and Disadvantages of Targeted Proteomics

      Targeted proteomics has emerged as a pivotal tool in modern biomedical research, extensively employed for disease diagnosis, treatment, and biomarker discovery. By concentrating on specific proteins for detailed analysis, researchers can glean comprehensive information about biological samples.

    • • Workflow of Targeted Proteomics

      Targeted proteomics is a method that employs specific mass spectrometry techniques to analyze predetermined proteins or peptide segments with high sensitivity and specificity. In contrast to global proteomics, targeted proteomics allows researchers to focus on a small number of specific targets, providing more precise data. The workflow generally includes the following key steps:

    • • Principle of Targeted Proteomics

      Targeted proteomics differs from traditional shotgun proteomics, which typically involves analyzing all detectable proteins in a sample through mass spectrometry. In contrast, targeted proteomics focuses on pre-selected target proteins that are often relevant to specific biological issues or diseases.

    • • Mechanism of Cellular Proteomics

      Cellular proteomics focuses not just on individual proteins but emphasizes the overall expression of proteins within a cell. By analyzing the abundance, variations, and interaction networks of proteins, it reveals the biological functions of the cell. Key technologies include Mass Spectrometry (MS), Protein Arrays, and bioinformatics.

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