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Printable Handouts
Navigable Slide Index
- Introduction
- Setting the scene
- MassBank: the beginning
- MassBank: distributed database model
- MassBank: crossing the world
- MassBank now
- NORMAN network and MassBank
- 2012: European MassBank
- Accessing literature spectra
- Supporting information in MassBank
- Confidence levels for tentative structures
- 2015: MassBank of North America
- MassBank and public data
- MassBank as a top contributor
- RMassBank
- Motivation
- Example of Orbitrap spectra
- Avoiding a “spectral dump”
- Recalibration curve
- Concept of RMassBank spectral processing
- RMassBank spectral processing steps
- RMassBank workflow: simple form
- RMassBank: clean-up and recalibration
- RMassBank: example clean-up
- RMassBank: multiplicity filtering
- RMassBank: spectrum annotation
- RMassBank with 70 Eawag pesticide spectra
- Processing pesticide spectra numbers
- Why databases are useful
- Usefulness in pesticide spectra example
- Formula annotation of high accuracy MS/MS
- Conclusions: RMassBank
- Many mass spectral resources
- SPLASH: an identifier for mass spectra
- SPLASH: communicate between libraries
- Mass spectral libraries for small molecules
- Acknowledgements
Topics Covered
- MassBank: an open access mass spectral library
- Sharing spectra worldwide
- Downloadable RMassBank
- Autocuration of MS/MS spectra
- Recalibration, noise reduction, annotation
- Upload of thousands of spectra
- Enhanced interpretation and identification
- SPLASH: communicate between all mass spectral resources
Links
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Talk Citation
Schymanski, E.L. (2017, October 31). MassBank and RMassBank [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved October 12, 2024, from https://doi.org/10.69645/XMER7970.Export Citation (RIS)
Publication History
Financial Disclosures
- Dr. Emma L. Schymanski has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
Other Talks in the Series: Bioinformatics for Metabolomics
Transcript
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0:00
Hello and welcome to my talk on MassBank and RMassBank.
My name is Emma Schymanski,
I'm a research scientist at Eawag,
the Swiss Federal Institute of Aquatic Science and Technology in Dubendorf, Switzerland.
0:13
Just to set the scene to this presentation,
this presentation is actually part of a series on
Bioinformatics for Metabolomics and forms Part D,
for Metabolomics Resources and Computational Tools.
And this talk being about MassBank and RMassBank actually covers both.
So, MassBank itself is an open access library of mass spectra,
and in this respect is a resource for identification of metabolites and small molecules.
RMassBank is actually an open source R package enabling data
upload into MassBank and computational tool to form part of this talk,
and this is aimed really at increasing the number of
publicly available mass spectra in MassBank and thus, also in the open space.
0:56
MassBank actually started in 2006,
as one of the first public repositories of mass spectra.
And you can see the website at the bottom of the slide,
and this screenshot here,
shows an overview of the database service from the MassBank website itself.
One of the strengths but also in some people's minds,
also one of the weaknesses of MassBank is that it had no standard analytical method.
This meant that MassBank was actually suitable for all types of data,
which in my opinion is actually a strength.
You can basically include many different types
of mass spectrum data so you can have gas chromatography,
liquid chromatography, mass spectra,
single scan mass spectra,
or tandem mass spectra, high resolution,
low resolution, and accurate mass data.
So, that's just going through, in order of the acronyms on the slide,
and the contributor is responsible for data quality,
which is in some cases a good thing and in
some cases not such a good thing and I will go through this in a few later slides.
If you want to read up more about MassBank itself,
then I'd recommend you look at the publication
that I've also got referenced on this slide.