摘要

Significant advances have been made over the past ten years to standardize the data emerging from the proteomic workflows adopted by laboratories all over the world. Differences in workflows, instrumentation, analysis software and reporting methods initially resulted in very disparate data being generated by many of these research groups, making data storage and comparison challenging. As the data standards proposed by the HUPO-PSI have increasingly been adopted, and tools and databases implementing these data formats have become more readily available, data generated by these complex experimental procedures is now becoming easier to manipulate, to visualize and to analyse. Public domain databases now exist to collate the information generated by experimentalists and to make the generation of specific protein expression maps, and monitoring of changes in protein expression levels in response to external stimuli a real possibility. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

  • 出版日期2014-1