Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification.

ABSTRACT:

Background

In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produce the 6- methyl salicylic acid polyketide molecule) for application in metabolic engineering.

Results

More than 450 metabolites were detected and subsequently used in the analysis. Our approach consists of two analytical steps of the metabolic profiling data, an initial non-linear unsupervised analysis with Self-Organizing Maps (SOM) to identify similarities and differences among the metabolic profiles of the studied strains, followed by a second, supervised analysis for training a classifier based on the selected biomarkers. Our analysis identified seven putative biomarkers that were able to cluste

SUBMITTER: Kouskoumvekaki I 

PROVIDER: S-EPMC2248563 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature