How to Search the Glycolipid data in "LIPIDBANK for Web" the Newly Developed Lipid Database in Japan.

Watanabe, K.; Yasugi, Etsuko; Oshima, Mieko

doi:10.4052/tigg.12.175

Cited by 64 publications

(43 citation statements)

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“…A number of repositories, such as GenBank, SwissProt, and ENSEMBL (http://www.ensembl.org), support nucleic acid and protein databases; however, there are only a few specialized databases [e.g., LIPIDAT (7) and Lipid Bank (8)] that provide a catalog, annotation, and functional classification of lipids. Given the importance of these molecules in cellular function and pathology, there is an imminent need for the creation of a well-organized database of lipids.…”

Section: Databasing Lipids Annotation and Functionmentioning

confidence: 99%

A comprehensive classification system for lipids

Fahy

Subramaniam

Brown

et al. 2005

Journal of Lipid Research

1,429

685

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Lipids are produced, transported, and recognized by the concerted actions of numerous enzymes, binding proteins, and receptors. A comprehensive analysis of lipid molecules, "lipidomics," in the context of genomics and proteomics is crucial to understanding cellular physiology and pathology; consequently, lipid biology has become a major research target of the postgenomic revolution and systems biology. To facilitate international communication about lipids, a comprehensive classification of lipids with a common platform that is compatible with informatics requirements has been developed to deal with the massive amounts of data that will be generated by our lipid community. As an initial step in this development, we divide lipids into eight categories (fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids, prenol lipids, saccharolipids, and polyketides) containing distinct classes and subclasses of molecules, The goal of collecting data on lipids using a "systems biology" approach to lipidomics requires the development of a comprehensive classification, nomenclature, and chemical representation system to accommodate the myriad lipids that exist in nature. Lipids have been loosely defined as biological substances that are generally hydrophobic in nature and in many cases soluble in organic solvents (1). These chemical properties cover a broad range of mole-

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Section: Databasing Lipids Annotation and Functionmentioning

confidence: 99%

A comprehensive classification system for lipids

Fahy

Subramaniam

Brown

et al. 2005

Journal of Lipid Research

1,429

685

View full text Add to dashboard Cite

show abstract

“…Examples are the LIPID BANK [39], the LIPIDAT [40,41], the LIPID MAPS Structure Database (LMSD) [42] and the CAPEC Lipids Database [43]. Experiments are costly and time-consuming but experimental data form the basis of prediction models and parameter regressions.…”

Section: Experimental Measurementsmentioning

confidence: 99%

Beyond biofuels: economic opportunities, recent advances and challenges in property modeling for vegetable oils

Santos

Gerbaud

Roux

2014

Green Processing and Synthesis

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Despite the greater attention given to biofuels application in the literature, there are many economic and environmental drivers to use vegetables oils (VOs) as a renewable feedstock for other applications. These drivers are discussed in the present work and the technological challenges imposed by this shift towards new VOs uses are also discussed. They are mainly associated to the reaction routes issues, the performance regarding enduser properties, experimental procedures and property prediction models. The need for more holistic approaches (life cycle analysis) is briefly discussed and the potential benefits arising from new computer-aided tools are highlighted as well.

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“…This may include tools for automated data processing [7][8][9][10][11] and lipid identification and mining [12][13][14]. • Statistical data analysis: As for other omics data, high dimensionality of typical lipidomics datasets demands careful statistical analysis.…”

Section: Introductionmentioning

confidence: 99%