| Resumo: | One of the major challenges of today's biotechnology is to be able to obtain the maximum of metabolic information for the holistic interpretation of biological systems. Herein we present a new computational application for gas-chromatography mass spectroscopy automated signal processing, named 'X-Metabolomics', that shows to be a potential framework for dynamic systems as fermentation processes interpretation by compounds and pathways identification and quantification and moreover for new metabolites discovery. Our GC-MS signal processing pipeline is implemented into an X-window interface using Tcl/Tk interface and based on R statistical programming environment for comprehensive statistical computing of results and access to 'Bioconductor' bioinformatics platform under Unix, Linux and MacOS. This approach focuses on the robustness of peak extraction algorithms for further identification, quantification and biological interpretation by multivariate analysis, evolving the following steps: i) peaks extraction; ii) supervised filtering; iii) identification of candidate fragments and removal of possible contaminants; iv) compounds identification/quantification; v) compounds expression and co-expression in time-course; and vi) sample classification and biological interpretation by multivariate analysis. 'X-Metabolomics' can be an useful tool in different fields such as pharmacology, genetics, living cells systems, promising to be innovative and very helpful for new drug discovery and new advances in dynamic systems understanding.
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