One of the fundamental aims of life science is to gain insights into the functioning of an organism at systems
level. Generation and systematic storage of enormous biological data in the post genomic era has made systems level
studies a reality. For studies involving systems level investigation, metabolic pathways data inferred from intricate
interactions amongst genes/enzymes/proteins are best suited and are being used extensively as they represent dynamic
interactions in an organism. Consequently research in the field of comparative metabolomics as well as metabolic
networks analysis is undergoing rapid improvement. Although the efforts to analyze metabolome have increased in recent
years, our knowledge pertaining to its design principles is very limited. Various methodologies to compare and align
metabolic pathways have been put forth and are discussed in this review. Further, graph theoretic approaches are
undertaken with an aim to unveil the universal laws governing the complex metabolic networks. New algorithms that
negate the abstraction from earlier studies are the need of the hour. One such approach termed “metabolic categorization”
that helps in understanding the functionality of each metabolic pathway at systems level is discussed in this review.
Finally, extension of linguistic approaches from genome and proteome to metabolome is suggested in order to simplify
the understanding of a living system.
Keywords: Biological organization, metabolic categorization, metabolic networks analysis, metabolic pathways alignment,
modular organization, network properties.
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