Pathway Activity Profiling (PAPi): from the metabolite profile to the metabolic pathway activity
Author(s) -
Raphael Aggio,
Katya Ruggiero,
Silas G. VillasBôas
Publication year - 2010
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btq567
Subject(s) - metabolomics , metabolic pathway , metabolite , computer science , profiling (computer programming) , computational biology , pathway analysis , bioinformatics , biology , biochemistry , metabolism , gene , gene expression , operating system
Metabolomics is one of the most recent omics-technologies and uses robust analytical techniques to screen low molecular mass metabolites in biological samples. It has evolved very quickly during the last decade. However, metabolomics datasets are considered highly complex when used to relate metabolite levels to metabolic pathway activity. Despite recent developments in bioinformatics, which have improved the quality of metabolomics data, there is still no straightforward method capable of correlating metabolite level to the activity of different metabolic pathways operating within the cells. Thus, this kind of analysis still depends on extremely laborious and time-consuming processes.
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