Summary of Study ST001173
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000785. The data can be accessed directly via it's Project DOI: 10.21228/M86T1D This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Study ID | ST001173 |
| Study Title | Combinatorial metabolic mixtures for encoding abstract digital data |
| Study Type | MALDI MS |
| Study Summary | We present several kilobyte-scale image datasets stored in synthetic metabolomes, which are decoded with accuracy exceeding 98-99% using multi-mass logistic regression. |
| Institute | Brown University |
| Department | Engineering |
| Laboratory | Rosenstein Lab |
| Last Name | Kennedy |
| First Name | Eamonn |
| Address | Barus & Holley room 353, 184 Hope St |
| eamonn_kennedy@brown.edu | |
| Phone | 7737507192 |
| Submit Date | 2019-04-19 |
| Publications | E. Kennedy et al. “Encoding information in synthetic metabolomes” Plos One, accepted, 2019 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | hdf5 |
| Analysis Type Detail | MALDI-MS |
| Release Date | 2019-05-15 |
| Release Version | 1 |
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Subject:
| Subject ID: | SU001239 |
| Subject Type: | Synthetic |
| Subject Species: | Escherichia coli |
| Taxonomy ID: | 562 |
