کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1248280 | 1495895 | 2015 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics
ترجمه فارسی عنوان
استفاده از درختان درختی و درخت طیفی جرم برای شناسایی ترکیبات ناشناخته در متابولومیک
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی
Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemical diversity of metabolism is vast, making structure identification arduous and time consuming. Currently, comprehensive analysis of mass spectra in metabolomics is limited to library matching, but tandem mass spectral libraries are small compared to the large number of compounds found in the biosphere, including xenobiotics. Resolving this bottleneck requires richer data acquisition and better computational tools. Multi-stage mass spectrometry (MSn) trees show promise to aid in this regard. Fragmentation trees explore the fragmentation process, generate fragmentation rules and aid in sub-structure identification, while mass spectral trees delineate the dependencies in multi-stage MS of collision-induced dissociations. This review covers advancements over the past 10 years as a tool for metabolite identification, including algorithms, software and databases used to build and to implement fragmentation trees and mass spectral annotations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: TrAC Trends in Analytical Chemistry - Volume 69, June 2015, Pages 52-61
Journal: TrAC Trends in Analytical Chemistry - Volume 69, June 2015, Pages 52-61
نویسندگان
Arpana Vaniya, Oliver Fiehn,