Proteomics

Proteomics Research

The science of studying all proteins expressed by an organism, tissue, or cell at a specific time and under specific conditions, along with their structures, functions, interactions, and dynamic changes. It explores the impact of diseases, drugs, etc., on life processes and explains the mechanisms of gene expression regulation. The aim is to reveal the molecular basis of life activities and disease-related processes.

TMT-Quantitative Proteomics

A high-throughput method that uses isotope-labeled peptide probes to label, separate and quantify proteins in different samples through mass spectrometry technology. It can accurately compare the differences in protein expression levels under different biological conditions. TMT uses 6, 10, 16, and 18 isotope labels to simultaneously compare protein expression levels between 18 samples. TMT proteomics of NucleoSequence Biology has accurate quantitative analysis, extremely high repeatability, and identification depth.

Label-Free Quantitative Proteomics

Protein quantification technology that does not require chemical labeling. The mass spectrometry data generated when the peptide fragments of proteins are detected by liquid chromatography-mass spectrometry to analyze and identify proteins on a large scale. It is suitable for the detection of large clinical samples and can absolutely detect the "presence or absence" of proteins in the samples. The unique Label-free quantitative proteomics of NucleoSequence Biotechnology has higher ion utilization and accuracy, and can achieve high-sensitivity, high-throughput, and high-precision protein detection with less sample loading.

DIA Quantitative Proteomics

The data-independent scanning mode (DIA) is used to systematically scan all peptide ions in segments, so as to obtain information on all ions in the sample without omission or difference. It avoids some low-abundance proteins missed by data-dependent acquisition (DDA), thereby greatly improving the detection rate of proteins. It reduces the missing values of sample detection, improves quantitative accuracy and repeatability, and realizes highly stable and accurate proteome quantitative analysis in large sample cohorts. It is widely used in biomarker discovery and disease mechanism research.