LIPID MAPS online tools for lipid research
Nucleic Acids Res., 2007
866 citations recorded by the source corpus.
The LIPID MAPS consortium has developed a number of online tools for performing tasks such as drawing lipid structures and predicting possible structures from mass spectrometry (MS) data. A simple online interface has been developed to enable an end-user to rapidly generate a variety of lipid chemical structures, along with corresponding systematic names and ontological information. The structure-drawing tools are available for six categories of lipids: (i) fatty acyls, (ii) glycerolipids, (iii) glycerophospholipids, (iv) cardiolipins, (v) sphingolipids and (vi) sterols. Within each category, the structure-drawing tools support the specification of various parameters such as chain lengths at a specific sn position, head groups, double bond positions and stereochemistry to generate a specific lipid structure. The structure-drawing tools have also been integrated with a second set of online tools which predict possible lipid structures from precursor-ion and product-ion MS experimental data. The MS prediction tools are available for three categories of lipids: (i) mono/di/triacylglycerols, (ii) glycerophospholipids and (iii) cardiolipins. The LIPID MAPS online tools are publicly available at www.lipidmaps.org/tools/.
Subfields: Clinical Biochemistry, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/beb37468be7c9848fd5a8d450d3fece201dc999d
Citations in the corpus
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- HMDB 3.0—The Human Metabolome Database in 2013 (2012, background): “Furthermore, there are now a growing number of alternate chemical taxonomies being used by other databases, such as BioCyc/MetaCyc (15), ChEBI (11) and LipidMaps (6).”
- CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra (2014, background): “A number of web servers are available that allow MS / MS spectrum searches against computationally predicted spectra for molecules from specific chemical classes, e.g. proteins (17–19) and lipids (20).”
- The Human Serum Metabolome (2011, background): “With the release of the Human Metabolome Database (HMDB) [4,5] and other related compound or spectral resources such as KEGG [6], LipidMaps [7], PubChem [8], ChEBI [9], MMCD [10], Metlin [11] and MassBank [12], we believe the field has taken an important step towards making metabolomics studies much”
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- HMDB: a knowledgebase for the human metabolome (2008, background): “It is also worth noting that many of the most commonly used metabolite databases (KEGG, HumanCyc, BiGG or Lipid Maps) only list about one-fifth the number of metabolites found in the HMDB.”
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