Bioinformatics strategies in life sciences: from data processing and data warehousing to biological knowledge extraction

J Integr Bioinform. 2010 May 27;7(1):141. doi: 10.2390/biecoll-jib-2010-141.


With the large variety of Proteomics workflows, as well as the large variety of instruments and data-analysis software available, researchers today face major challenges validating and comparing their Proteomics data. Here we present a new generation of the ProteinScape bioinformatics platform, now enabling researchers to manage Proteomics data from the generation and data warehousing to a central data repository with a strong focus on the improved accuracy, reproducibility and comparability demanded by many researchers in the field. It addresses scientists; current needs in proteomics identification, quantification and validation. But producing large protein lists is not the end point in Proteomics, where one ultimately aims to answer specific questions about the biological condition or disease model of the analyzed sample. In this context, a new tool has been developed at the Spanish Centro Nacional de Biotecnologia Proteomics Facility termed PIKE (Protein information and Knowledge Extractor) that allows researchers to control, filter and access specific information from genomics and proteomic databases, to understand the role and relationships of the proteins identified in the experiments. Additionally, an EU funded project, ProDac, has coordinated systematic data collection in public standards-compliant repositories like PRIDE. This will cover all aspects from generating MS data in the laboratory, assembling the whole annotation information and storing it together with identifications in a standardised format.

MeSH terms

  • Biological Science Disciplines / methods*
  • Computational Biology / methods*
  • Databases as Topic
  • Electronic Data Processing*
  • Information Storage and Retrieval*
  • Knowledge
  • Peptides / analysis
  • Proteomics
  • Reproducibility of Results
  • Search Engine


  • Peptides