mass spectrometry
Definition
Mass spectrometry is an analytical technique used to identify and quantify proteins, peptides, and other biomolecules based on their mass-to-charge ratio. In proteomics, samples are ionized and fragmented, then analyzed by measuring the mass and abundance of resulting ions. This enables researchers to determine protein identity, post-translational modifications, protein-protein interactions, and relative or absolute protein abundance across samples. Mass spectrometry is fundamental to bottom-up proteomics (analyzing peptides) and top-down proteomics (analyzing intact proteins), providing comprehensive insights into cellular protein composition, dynamics, and functional states critical for understanding biological systems and disease mechanisms.
Visualize mass spectrometry in Nodes Bio
Researchers can visualize mass spectrometry proteomics data as protein-protein interaction networks, where nodes represent identified proteins and edges indicate physical interactions or co-expression patterns. Nodes Bio enables integration of quantitative abundance data with pathway annotations, allowing users to map differentially expressed proteins onto biological networks, identify enriched pathways, and explore how protein complexes change across experimental conditions or disease states.
Visualization Ideas:
- Protein-protein interaction networks colored by abundance fold-change from mass spec data
- Pathway enrichment maps showing which biological processes are affected by differentially expressed proteins
- Time-course networks displaying dynamic protein expression changes across multiple mass spec experiments
Example Use Case
A cancer research team uses mass spectrometry to profile protein expression in drug-resistant versus drug-sensitive tumor cells. They identify 2,500 proteins with significant abundance changes. By importing this data into Nodes Bio, they visualize how resistance-associated proteins cluster into functional networks, revealing that upregulated proteins converge on DNA repair pathways and drug efflux mechanisms. This network view helps prioritize combination therapy targets that could overcome resistance by simultaneously disrupting multiple interconnected pathways.