Figure 1

The placement of PeptideAtlas. The placement of PeptideAtlas bridging global and targeted proteomics experiments is depicted. Protein extracts were prepared from diverse in vivo and in vitro samples. The proteins were digested and, after additional fractionation steps, analyzed via LC-MS/MS. The spectra were mapped to peptides that likely gave rise to them using sequence database searching. Subsequently, the mappings were statistically validated. Spectral centric data mining was facilitated by a relational database (SBEAMS). Then, re-organization of the data in a peptide-centric manner was the focus during PeptideAtlas construction: Data accumulated over many experiments, generated over the course of several months or years, was complexity-reduced and condensed concentrating on the actual peptide entities. This now allows for retrieval of high quality proteotypic peptides as well as for gene model validation based on expressed peptide sequences.