Abstract
Proteomics has the capability to generate overwhelming quantities of data in relatively short timescales, and it is not uncommon to see experimenters investing substantially more time in data analysis than in data gathering. Although several sophisticated tools for data reduction and analysis are available, they lack the flexibility to cope with increasingly innovative experimental strategies and new database resources that encode both qualitative and quantitative data. I will outline a specification of a flexible proteomics tool that could address many current bottlenecks and deficiencies.