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What is proteomics and why does it matter? The human genome serves as the blueprint for who we are—dictating traits like hair color and predisposition to certain diseases. While genomics, the study of our genes, provides invaluable insights into our genetic makeup, it is the proteins that are the functional molecules in our cells and execute these genetic instructions, performing essential tasks that keep us alive and healthy.‍Unlike the relatively stable genome, the proteome—the entire set of proteins produced by an organism—is highly dynamic and reflects the body’s current state, responding to external signals such as food intake or infection by pathogens.

Biology has fully embraced big-data, high-throughput approaches, and data workflows (Figure below) have become indispensable for processing, analyzing, understanding, and enabling new discoveries. These workflows begin with the interpretation of raw signals from laboratory instruments, such as DNA sequencers and mass spectrometers, and proceed through multiple steps of aggregation and filtering. This preprocessing stage transforms complex data into a biologically interpretable form, such as mutations statuses or levels of gene transcripts and proteins, and sets the stage for modeling and analysis. The data modeling and analysis stage uses various data science approaches to generate new insights into functioning of living organisms or finding drivers of disease that could potentially turn into new drugs, drug targets, or clinical biomarkers.