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Modeling the course of amyotrophic lateral sclerosis

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An Erratum to this article was published on 12 May 2015

This article has been updated

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

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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.

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Authors and Affiliations

  1. Christina Fournier and Jonathan D. Glass are at Emory University School of Medicine, Atlanta, Georgia, USA.,

    Christina Fournier & Jonathan D Glass

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  1. Christina Fournier
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  2. Jonathan D Glass
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Correspondence to Jonathan D Glass.

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The authors declare no competing financial interests.

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

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