ISDB: In Silico Spectral Databases of Natural Products
Pierre-Marie Allard and Jonathan Bisson and Adriano Rutz

folder 8287341 (4 files)
fileisdb_neg.mgf 753.26MB
fileisdb_neg_cleaned.pkl 723.23MB
fileisdb_pos.mgf 1.00GB
fileisdb_pos_cleaned.pkl 940.62MB
Type: Dataset

Metadata:
@article{,
title= {ISDB: In Silico Spectral Databases of Natural Products},
journal= {},
author= {Pierre-Marie Allard and Jonathan Bisson and Adriano Rutz},
year= {},
url= {https://doi.org/10.5281/zenodo.8287341},
abstract= {An In Silico spectral DataBase (ISDB) of natural products calculated from structures aggregated in the frame of the LOTUS Initiative (https://doi.org/10.7554/eLife.70780).
Fragmented using cfm-predict 4 (https://doi.org/10.1021/acs.analchem.1c01465) .
In silico spectral database preparation and use for dereplication initially described in Integration of Molecular Networking and In-Silico MS/MS Fragmentation for Natural Products Dereplication https://doi.org/10.1021/ACS.ANALCHEM.5B04804
See https://github.com/mandelbrot-project/spectral_lib_builder for associated building scripts.
See https://github.com/mandelbrot-project/spectral_lib_matcher for associated matching scripts.
The pickle formated ISDBs are build for quicker loading via matchms.},
keywords= {mass spectrometry, metabolomics, metabolite annotation, spectral database, natural products},
terms= {},
license= {CC0},
superseded= {}
}

Citation:
Allard, P., Bisson, J., & Rutz, A.. (2025). ISDB: In Silico Spectral Databases of Natural Products [Data set]. Academic Torrents. https://academictorrents.com/details/ab530b4e6493c7e7c5539b65cdbe84263d15b4e6
No stats to report yet.

Send Feedback Start
   0.000009
DB Connect
   0.000781
Lookup hash in DB
   0.000491
Get torrent details
   0.000139
Get torrent details, finished
   0.000279
Get authors
   0.000030
Parse bibtex
   0.000146
Write header
   0.000283
get stars
   0.000125
home tab
   0.000307
render right panel
   0.000006
render ads
   0.000468
fetch current hosters
   0.000256
Start get stats
   0.002933
End get stats
   0.000002
related datasets
   0.007579
Done