Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

KinomeXplorer: an integrated platform for kinome biology studies

Nature Methods volume 11, pages 603–604 (2014)Cite this article

Subjects

To the Editor:

The generation of large-scale phosphoproteomics data sets to elucidate the phosphorylation events associated with a given phenotype or disease condition has become routine. To fully utilize the power of such data sets, tools to deconvolute the underlying intracellular signaling networks are required. Here we present KinomeXplorer (http://KinomeXplorer.info/), an integrated platform for modeling kinase signaling networks by combining sequence specificity with cellular context.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Overview of the improved NetworKIN algorithm in KinomeXplorer.

References

  1. Seet, B.T., Dikic, I., Zhou, M.M. & Pawson, T. Nat. Rev. Mol. Cell Biol. 7, 473–483 (2006).

    Article  CAS  Google Scholar 

  2. Lim, W.A. & Pawson, T. Cell 142, 661–667 (2010).

    Article  CAS  Google Scholar 

  3. Davis, M.I. et al. Nat. Biotechnol. 29, 1046–1051 (2011).

    Article  CAS  Google Scholar 

  4. Anastassiadis, T., Deacon, S.W., Devarajan, K., Ma, H. & Peterson, J.R. Nat. Biotechnol. 29, 1039–1045 (2011).

    Article  CAS  Google Scholar 

  5. Dinkel, H. et al. Nucleic Acids Res. 39, D261–D267 (2011).

    Article  CAS  Google Scholar 

  6. Linding, R. et al. Cell 129, 1415–1426 (2007).

    Article  CAS  Google Scholar 

  7. Janes, K.A. et al. Science 310, 1646–1653 (2005).

    Article  CAS  Google Scholar 

  8. Yaffe, M.B. Sci. Signal. 6, pe13 (2013).

    PubMed  Google Scholar 

  9. Miller, M.L. et al. Sci. Signal. 1, ra2 (2008).

    Article  Google Scholar 

  10. Gough, N.R. Sci. Signal. 6, eg3 (2013).

    PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank members of R.L.'s laboratory for useful input on the manuscript, and A. Pasculescu for input on the data collection. This work was supported by the Lundbeck Foundation, the Human Frontier Science Program (HFSP), the Danish Council for Independent Research (FSS) and the European Research Council (ERC).

Author information

Author notes

  1. Heiko Horn, Erwin M Schoof and Jinho Kim: These authors contributed equally to this work.

Authors and Affiliations

  1. Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark

    Heiko Horn & Lars Juhl Jensen

  2. Department of Systems Biology, Cellular Signal Integration Group (C-SIG), Center for Biological Sequence Analysis (CBS), Technical University of Denmark (DTU), Lyngby, Denmark

    Erwin M Schoof, Jinho Kim, Xavier Robin & Rune Linding

  3. Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, USA

    Martin L Miller

  4. Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

    Francesca Diella

  5. Molecular Health GmbH, Heidelberg, Germany

    Francesca Diella

  6. Department of Biology, University of Rome Tor Vergata, Rome, Italy

    Anita Palma & Gianni Cesareni

  7. Istituto Ricovero e Cura a Carattere Scientifico, Fondazione Santa Lucia, Rome, Italy

    Gianni Cesareni

Authors
  1. Heiko Horn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Erwin M Schoof
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jinho Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xavier Robin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Martin L Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Francesca Diella
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Anita Palma
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Gianni Cesareni
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Lars Juhl Jensen
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Rune Linding
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Lars Juhl Jensen or Rune Linding.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1 and 2, and Supplementary Note (PDF 757 kb)

Supplementary Table 1

Benchmark of the NetworKIN method (XLS 44 kb)

Supplementary Table 2

Dataset for training NetPhorest and NetworKIN (XLS 3640 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Horn, H., Schoof, E., Kim, J. et al. KinomeXplorer: an integrated platform for kinome biology studies. Nat Methods 11, 603–604 (2014). https://doi.org/10.1038/nmeth.2968

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.2968

This article is cited by

Search

Advanced search

Quick links

Nature Briefing AI and Robotics

Sign up for the Nature Briefing: AI and Robotics newsletter — what matters in AI and robotics research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: AI and Robotics