LipidBlast - in-silico tandem mass spectrometry database for lipid identification

By Tobias Kind, Kwang-Hyeon Liu, Do Yup Lee, Brian C. DeFelice, John K. Meissen, Oliver Fiehn. Nature Methods, 2013

905 citations recorded by the source corpus.

Current tandem mass spectral libraries for lipid annotations in metabolomics are limited in size and diversity. We provide a freely available computer-generated tandem mass spectral library of 212,516 spectra covering 119,200 compounds from 26 lipid compound classes, including phospholipids, glycerolipids, bacterial lipoglycans and plant glycolipids. We show platform independence by using tandem mass spectra from 40 different mass spectrometer types including low-resolution and high-resolution instruments.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/9bd2fd556fb2e4f40f757beb37e334ffcf2e48b7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Alexandra C. Schrimpe-Rutledge
2. J. McLean
3. Sebastian Böcker
4. S. Sherrod
5. S. Codreanu
6. David S. Wishart

In Spectroscopy

1. Sebastian Böcker
2. David S. Wishart

Citations in the corpus

• Searching molecular structure databases with tandem mass spectra using CSI:FingerID (2015, methodology): “Structural elucidation remains a challenging problem, in particular for compounds that cannot be found in any spectral library (1): In total, all available spectral MS/MS libraries of pure chemical standards cover fewer than 20,000 compounds (5).”
• Untargeted metabolomics strategies – Challenges and Emerging Directions (2016, background): “Analyte identification can be performed by searching the experimental MS1 or MS/MS data through databases available to the public for free (e.g., ChemSpider (http://www.chemspider.com), METLIN [15], Human Metabolome DataBase (HMDB) [16], MassBank [17], mzCloud (https://www.mzcloud.org), GNPS (http:/”