Proteomics is the large scale study of all proteins in a cell, tissue or organism, including their structures, functions and interactions. Compared to genomics, which looks at relatively stable DNA, proteomics targets a dynamic and context dependent layer of biology. Protein levels and modifications change with cell type, development, environment and disease, so proteomic data can capture the current state of a biological system.

Modern proteomics relies heavily on high resolution mass spectrometry. In a typical workflow, proteins are extracted from a sample, enzymatically digested into peptides, separated by liquid chromatography and then analyzed in a mass spectrometer. The instrument measures peptide masses and fragmentation patterns, which are matched to protein sequences using computational search engines. Quantitative approaches such as label free quantification or stable isotope labeling enable comparison of protein abundances across samples.

Beyond simple identification and quantification, researchers study post translational modifications like phosphorylation, glycosylation and ubiquitination, which regulate signaling pathways and protein stability. Interaction proteomics maps protein complexes and networks, revealing how cellular functions emerge from coordinated protein activity.

Key applications include biomarker discovery for early disease detection, stratification of patients and monitoring of treatment response. In oncology, for example, proteomic signatures can distinguish tumor subtypes or predict drug sensitivity. In microbiology and ecology, proteomics helps characterize microbial communities and host pathogen interactions. In agriculture and food science, it is used to improve crop resilience, assess food quality and detect contaminants.

Ongoing advances in instrumentation, sample preparation and data analysis are improving sensitivity, coverage and throughput, bringing proteomics closer to routine clinical and industrial use.