Summary of Study ST002045
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 PR001292. The data can be accessed directly via it's Project DOI: 10.21228/M8Q70T This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
Study ID | ST002045 |
Study Title | massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation |
Study Summary | The patient-derived xenograft (PDX) mouse brain tumor model of glioblastoma (GBM) samples were analyzed by 2D MALDI FT ICR MSI. |
Institute | Brigham and Women's Hospital |
Department | Department of Neurosurgery |
Laboratory | Nathalie Y.R. Agar |
Last Name | Abdelmoula |
First Name | Walid |
Address | 60 Fenwood RD, Boston, MA |
wahassan@bwh.harvard.edu | |
Phone | 8572149765 |
Submit Date | 2021-12-06 |
Raw Data Available | Yes |
Raw Data File Type(s) | h5 |
Analysis Type Detail | MALDI-MS |
Release Date | 2022-01-04 |
Release Version | 1 |
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Collection:
Collection ID: | CO002120 |
Collection Summary: | As stated in the massNetpaper: Briefly, 8 GBM tissue sections of 12 μm thickness were prepared and analyzed using a 9.4 Tesla SolariX mass spectrometer (Bruker Daltonics, Billerica, MA) in the positive ion mode with spatial resolution of 100 μm. The MSI data was exported from SCiLS lab 2020a (Bruker, Bremen, Germany) in the standardized format imzML (Race et al., 2012) and converted to the HDF5 format (Folk et al., 2011) for deep learning analysis. |
Sample Type: | PDX GBM - mouse brain tumor section |