Biomedical informatics for proteomics.

Abstract

Success in proteomics depends upon careful study design and high-quality biological samples. Advanced information technologies, and also an ability to use existing knowledge to the full, will be crucial in making sense of the data. Despite its genome-scale potential, proteome analysis is at a much earlier stage of development than genomics and gene expression (microarray) studies. Fundamental issues involving biological variability, pre-analytic factors and analytical reproducibility remain to be resolved. Consequently, the analysis of proteomics data is currently informal and relies heavily on expert opinion. Databases and software tools developed for the analysis of molecular sequences and microarrays are helpful, but are limited owing to the unique attributes of proteomics data and differing research goals.