A large number of mass spectra from different samples have been collected, and to identify small molecules from these spectra, database searches are needed, which is challenging. Here, the authors report molDiscovery, a mass spectral database search method that uses an algorithm to generate mass spectrometry fragmentations and learns a probabilistic model to match small molecules with their mass spectra
Tandem Mass Spectrometry (MS/MS) fragmentation patterns serve as a reproducible fingerprint for smal...
# The Author(s) 2010. This article is published with open access at Springerlink.com Abstract The st...
Competitive Fragmentation Modeling for Metabolite Identification (CFM-ID) is a machine learning tool...
The identification of small molecules from mass spectrometry (MS) data remains a major challenge in ...
Mass spectrometry allows sensitive, automated, and high-throughput analysis of small molecules. In p...
Source data of "molDiscovery: Learning Mass Spectrometry Fragmentation of Small Molecules
The 'inverse problem' of mass spectrometric molecular identification ('given a mass spectrum, calcul...
Abstract Background Mass spectrometry has become the analytical method of choice in metabolomics res...
Non-targeted analysis using high-resolution mass spectrometry is becoming a critical tool for identi...
Mass spectrometry is an important analytical technology for the identification of metabolites and sm...
Metabolites are small molecules involved in biological process of organisms. For example, ethylene s...
The identification of small molecules, such as metabolites, in a high throughput manner plays an imp...
Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra f...
Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpret...
Three programs were assessed for their ability to predict mass spectral fragmentation patterns for a...
Tandem Mass Spectrometry (MS/MS) fragmentation patterns serve as a reproducible fingerprint for smal...
# The Author(s) 2010. This article is published with open access at Springerlink.com Abstract The st...
Competitive Fragmentation Modeling for Metabolite Identification (CFM-ID) is a machine learning tool...
The identification of small molecules from mass spectrometry (MS) data remains a major challenge in ...
Mass spectrometry allows sensitive, automated, and high-throughput analysis of small molecules. In p...
Source data of "molDiscovery: Learning Mass Spectrometry Fragmentation of Small Molecules
The 'inverse problem' of mass spectrometric molecular identification ('given a mass spectrum, calcul...
Abstract Background Mass spectrometry has become the analytical method of choice in metabolomics res...
Non-targeted analysis using high-resolution mass spectrometry is becoming a critical tool for identi...
Mass spectrometry is an important analytical technology for the identification of metabolites and sm...
Metabolites are small molecules involved in biological process of organisms. For example, ethylene s...
The identification of small molecules, such as metabolites, in a high throughput manner plays an imp...
Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra f...
Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpret...
Three programs were assessed for their ability to predict mass spectral fragmentation patterns for a...
Tandem Mass Spectrometry (MS/MS) fragmentation patterns serve as a reproducible fingerprint for smal...
# The Author(s) 2010. This article is published with open access at Springerlink.com Abstract The st...
Competitive Fragmentation Modeling for Metabolite Identification (CFM-ID) is a machine learning tool...