Bioinformatic Tools in Crop Improvement - Crop Improvement: New Approaches and Modern Techniques - page 90

Table 2.9 (continued)

Database Name Plant Species/Purpose Uniform Resource Locator (URL)

SOMA | Self Organizing
Map Application Site

A web tool used in DNA
and protein fragment
classification

http://soma.arb-silva.de/

Recent advances from the
F1000 Biology Reports

Research article on the web
describing recent advances
in metabolomics and
greener pastures (ie in
plant biology)

http://f1000.com/reports/b/2/7/

trum data sets that are associated with particular compounds are used as metabolic
profiles for each compound.

Statistics (PCA-HC-SOM)

Data analysis is most important in determination of biological significance in
metabolomics. Statistical analyses using multivariate analysis, such as principal
component analysis (PCA), hierarchical clustering analysis (HCA) and self-orga-
nization mapping (SOM), are typically used to classify samples and/or metabolites
(Hirai et al. 2004 ; Jonsson et al. 2004 ; Matsuda et al. 2009 ). The visualization of
metabolic profiles on metabolic maps is also used in combination with other 'omics'
methods, which can include gene expression profiles of particular genes encoding
the enzymes involved in those particular pathways (Thimm et al. 2004 ; Tokimatsu
et al. 2005 ).

MetaboliteProfilingPlants

The systematic collection of metabolite profiles is the initial step in metabolomics.
This step can be performed with various instruments (described above) capable of
high turnover and simultaneously many measurements. Comprehensive metabolic
profile data can contribute to the understanding of the cellular system in response to
changes in intracellular and extracellular metabolites. Furthermore, the changes in
metabolic pathways associated with genetic variations can be evaluated as chemical
fingerprints to identify genes involved in metabolism. A number of studies of meta-
bolic profiling in plant species have been performed that have resulted in the release
of results; unfortunately these results are mostly present on web databases. Listed
below are the most important web-based sites for metabolite and product analysis,
their purpose and URL are detailed in Table 2.10 .