In the post genome era, various -OMICS areas of research have lead to the
generation of large amount of biological data which have brought us closer
to understanding the molecular mechanism of life. Metabolite Profiling is
newly emerging area of computational biology research which deals with
detection of set of metabolites (small chemical entities) in living
organisms which can be used to detect the genotypic causes for a metabolic
phenotype and explain perturbation effects. In the order of complexity,
there are now advanced methods available which can detect the intracellular
metabolites with high degree of sensitivity. In the present seminar, we
will give a comprehensive survey of the computational methods which are
currently being applied to these datasets with the focus to predict protein
function, for example pattern recognition methods, agglomerative methods,
constraint based methods, mathematical modeling of cell, simulation etc,
in Metabolomics.