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mzAPI: a new strategy for efficiently sharing mass spectrometry data

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Figure 1: Array scanners, telescopes and mass spectrometers: XML, HDF or API? (a) Although both DNA and protein can be extracted from biological samples, subsequent large-scale analyses (microarray or proteomics) yield data structures that diverge with respect to typical access patterns.

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Acknowledgements

We thank Y. Zhang and S. Ficarro for valuable discussion and input, and E. Smith for preparing the figure. This work was supported by the Dana-Farber Cancer Institute and the National Human Genome Research Institute (P50HG004233).

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Authors and Affiliations

  1. Department of Cancer Biology and Blais Proteomics Center, Dana-Farber Cancer Institute, Boston, Massachusetts, USA

    Manor Askenazi, Jignesh R Parikh & Jarrod A Marto

  2. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA

    Manor Askenazi & Jarrod A Marto

  3. Department of Biological Chemistry, The Hebrew University of Jerusalem, Jerusalem, Israel

    Manor Askenazi

  4. Bioinformatics Program, Boston University, Boston, Massachusetts, USA

    Jignesh R Parikh

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  1. Manor Askenazi
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  2. Jignesh R Parikh
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Askenazi, M., Parikh, J. & Marto, J. mzAPI: a new strategy for efficiently sharing mass spectrometry data. Nat Methods 6, 240–241 (2009). https://doi.org/10.1038/nmeth0409-240

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