The Challenges of Interpreting Phosphoproteomics Data: A Critical View Through the Bioinformatics Lens

  • Panayotis Vlastaridis
  • Stephen G. Oliver
  • Yves Van de Peer
  • Grigoris D. Amoutzias
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9874)


During the last decade, there has been great progress in high-throughput (HTP) phosphoproteomics and hundreds or even thousands of phosphorylation sites (p-sites) can now be detected in a single experiment. This success is attributable to a combination of very sensitive Mass Spectrometry instruments, better phosphopeptide enrichment techniques and bioinformatics software that are capable of detecting peptides and localizing p-sites. These new technologies have opened up a whole new level of gene regulation to be studied, with great potential for therapeutics and synthetic biology. Nevertheless, many challenges remain to be resolved; these concern the biases and noise of these proteomic technologies, the biological noise that is present, as well as the incompleteness of the current datasets. Despite these problems, the datasets published so far appear to represent a good sample of a complete phosphoproteome of some organisms and are capable of revealing their major properties.


Phosphoproteomics Phosphorylation Bioinformatics Data integration 



This work is supported and implemented under the “ARISTEIA ΙΙ” Action of the “operational programme education and lifelong learning” and is co-funded by the European Social Fund (ESF) and National Resources (code 4288 to G.D.A). G.D.A acknowledges additional support by research grants from the Postgraduate Programme ‘Applications of Molecular Biology-Genetics, Diagnostic Biomarkers’, code 3817 of the Department of Biochemistry & Biotechnology, University of Thessaly, Greece. S.G.O. acknowledges support from the Wellcome Trust (grant no. 104967/Z/14/Z). Y.V.d.P acknowledges the Multidisciplinary Research Partnership “Bioinformatics: from nucleotides to networks” Project (no. 01MR0310 W) of Ghent University.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Panayotis Vlastaridis
    • 1
  • Stephen G. Oliver
    • 2
  • Yves Van de Peer
    • 3
    • 4
    • 5
  • Grigoris D. Amoutzias
    • 1
  1. 1.Bioinformatics Laboratory, Department of Biochemistry and BiotechnologyUniversity of ThessalyLarisaGreece
  2. 2.Department of Biochemistry, Cambridge Systems Biology CentreUniversity of CambridgeCambridgeUK
  3. 3.Department of Plant Systems Biology, VIB, Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
  4. 4.Bioinformatics Institute GhentGhentBelgium
  5. 5.Department of Genetics, Genomics Research InstituteUniversity of PretoriaPretoriaSouth Africa

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