From: Recent advances in proteomics and metabolomics in plants
Tool name | Function characterization | Reference |
---|---|---|
IIMN | A tool integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. | (Schmid et al. 2021) |
NetID | An algorithm optimizes a network of mass spectrometry peak connections based on MS1 mass differences corresponding to the gain or loss of relevant chemical moieties, and MS2 spectral similarity. | (Chen et al. 2021) |
Qemistree | A tree-based approach for computing and representing chemical features from tandem MS-based metabolomics studies, which is based on the hierarchical organization of molecular fingerprints predicted from MS/MS fragmentation spectra. | (Tripathi et al. 2021) |
FBMN | A method that bridges popular MS data processing tools for LC-MS/MS and molecular networking analysis on GNPS, enabling the characterization of isomers, incorporation of relative quantification, and integration of ion mobility data. | (Nothias et al. 2020) |
CliqueMS | A computational tool that annotates redundant MS1 features by constructing a similarity network between coelution profiles and a calculated natural frequency of adduct formation observed in real complex biological samples and pure compounds, which produces accurate annotations for a single MS1 spectrum. | (Senan et al. 2019) |
MetWork | An annotation propagation tool, which based on MS2 data, organized in molecular network, a collaborative library of reactions, and a MS2 spectra prediction module. | (Beauxis et al. 2019) |
MetDNA | A metabolic reaction network-based recursive algorithm that characterizes initial seed metabolites with MS2 spectra, and utilizes their experimental MS2 spectra as surrogate spectra to annotate their reaction-paired neighbor metabolites. | (Shen et al. 2019) |
SIRIUS 4 | A tool integrates high-resolution isotope pattern analysis and fragmentation trees to provide an assessment of molecular structures from MS2 data for large datasets and propagation of annotation through molecular networks. | (Duhrkop et al. 2019) |
MolNetEnhancer | A software package that unites the output of several tools, including mass spectral molecular networking, unsupervised substructure discovery, and in silico structure annotation to illuminate structural details for each fragmentation spectrum. | (Ernst et al. 2019) |
DEREPLICATOR + | A tool for search the entire GNPS and identifies variants of known metabolites using molecular networking, which improves the identification of peptidic natural products, polyketides, terpenes, benzenoids, alkaloids, flavonoids, etc. | (Mohimani et al. 2018) |
NAP | An on-line tool that uses a combination of molecular networks, based on spectral similarity, together with in silico fragmentation, to enable the scientific community to strengthen their MS annotations. | (da Silva et al. 2018) |
DEREPLICATOR | A new dereplication algorithm that searches MS/MS spectral datasets against the database of peptidic natural products (PNPs), which enables high-throughput PNPs identification based on molecular networking. | (Mohimani et al. 2017) |
MS2LDA | An unsupervised method that extracts common patterns of mass fragments and neutral losses-Mass2Motifs from the collection of fragmentation spectra, which can be used to annotate molecules. | (van der Hooft et al. 2016) |
ISDB | An innovative dereplication strategy based on the combination of molecular networking with an extensive in-silico MS2 fragmentation database of natural products. | (Allard et al. 2016) |
GNPS | An open-access knowledge base for community-wide organization and sharing of raw, processed or identified MS2 spectrometry data. | (Wang et al. 2016) |