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BMCBI
2008
135views more  BMCBI 2008»
13 years 4 months ago
Facilitating the development of controlled vocabularies for metabolomics technologies with text mining
Background: Many bioinformatics applications rely on controlled vocabularies or ontologies to consistently interpret and seamlessly integrate information scattered across public r...
Irena Spasic, Daniel Schober, Susanna-Assunta Sans...
BMCBI
2007
106views more  BMCBI 2007»
13 years 4 months ago
Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logari
Background: Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend up...
Helen M. Parsons, Christian Ludwig, Ulrich L. G&uu...
BMCBI
2007
101views more  BMCBI 2007»
13 years 4 months ago
Statistical validation of megavariate effects in ASCA
Background: Innovative extensions of (M) ANOVA gain common ground for the analysis of designed metabolomics experiments. ASCA is such a multivariate analysis method; it has succes...
Daniel J. Vis, Johan A. Westerhuis, Age K. Smilde,...
BMCBI
2010
112views more  BMCBI 2010»
13 years 4 months ago
The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datas
Background: Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid c...
Adam J. Carroll, Murray R. Badger, A. Harvey Milla...
BIB
2007
53views more  BIB 2007»
13 years 4 months ago
Current Progress in computational metabolomics
Being a relatively new addition to the ‘omics’ field, metabolomics is still evolving its own computational infrastructure and assessing its own computational needs. Due to its...
David S. Wishart
ALMOB
2008
112views more  ALMOB 2008»
13 years 4 months ago
Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps
Background: One of the goals of global metabolomic analysis is to identify metabolic markers that are hidden within a large background of data originating from high-throughput ana...
Peter Meinicke, Thomas Lingner, Alexander Kaever, ...