Modeling the course of amyotrophic lateral sclerosis

Article metrics

  • An Erratum to this article was published on 12 May 2015

Large-scale computational analysis of patient data leads to better models of disease progression.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: ALS disease progression is highly variable among patients.
Figure 2: Design of the DREAM challenge to identify algorithms that predict ALS disease progression1.

Change history

  • 30 April 2015

    In the version of this article initially published, the number of patients said to be included in the PRO-ACT database was given as 1,822. There are 8,635 patients in the database to date, of which 1,822 were included in the crowdsourcing challenge. The error has been corrected in the HTML and PDF versions of the article.

References

  1. 1

    Küffner, R. et al. Nat. Biotechnol. 33, 51–57 (2015).

  2. 2

    Glass, J.D. Exp. Neurol. 233, 112–117 (2012).

  3. 3

    Abramson, V. & Arteaga, C.L. Clin. Cancer Res. 17, 952–958 (2011).

  4. 4

    Atassi, N. et al. Neurology 83, 1719–1725 (2014).

  5. 5

    Bedlack, R.S., Pastula, D.M., Welsh, E., Pulley, D. & Cudkowicz, M.E. Amyotroph. Lateral Scler. 9, 257–265 (2008).

Download references

Author information

Correspondence to Jonathan D Glass.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Fournier, C., Glass, J. Modeling the course of amyotrophic lateral sclerosis. Nat Biotechnol 33, 45–47 (2015) doi:10.1038/nbt.3118

Download citation

Further reading