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.

  • This Month
  • Published:

Points of Significance

Bayesian networks

Nature Methods volume 12, pages 799–800 (2015)Cite this article

Subjects

Abstract

For making probabilistic inferences, a graph is worth a thousand words.

Access through your institution
Buy or subscribe

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

Relevant articles

Open Access articles citing this article.

Access options

Access through your institution

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: Bayesian network of regulation between five genes.
Figure 2: Observing the state of a node can change the estimate of the states of other nodes.
Figure 3: Observation about child nodes creates conditional dependencies and independencies between its parent nodes on different paths.

References

  1. Needham, C.J., Bradford, J.R., Bulpitt, A.J. & Westhead, D.R. PLoS Comput. Biol. 3, e129 (2007).

    Article  Google Scholar 

  2. Beaumont, M.A. & Rannala, B. Nat. Rev. Genet. 5, 251–261 (2004).

    Article  CAS  Google Scholar 

  3. Puga, J.L., Krzywinski, M. & Altman, N. Nat. Methods 12, 277–278 (2015).

    Article  CAS  Google Scholar 

  4. Nagarajan, R., Scutari, M. & Lèbre, S. Bayesian Networks in R with Applications in Systems Biology (Springer, 2013).

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Jorge López Puga is a Professor of Research Methodology at Universidad Católica de Murcia (UCAM).,

    Jorge López Puga

  2. Martin Krzywinski is a staff scientist at Canada's Michael Smith Genome Sciences Centre.,

    Martin Krzywinski

  3. Naomi Altman is a Professor of Statistics at The Pennsylvania State University.,

    Naomi Altman

Authors
  1. Jorge López Puga
    View author publications

    Search author on:PubMed Google Scholar

  2. Martin Krzywinski
    View author publications

    Search author on:PubMed Google Scholar

  3. Naomi Altman
    View author publications

    Search author on:PubMed Google Scholar

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Puga, J., Krzywinski, M. & Altman, N. Bayesian networks. Nat Methods 12, 799–800 (2015). https://doi.org/10.1038/nmeth.3550

Download citation

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/nmeth.3550

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

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