title: Comparative systems biology: from bacteria to man.
abstract: Comparative analyses, as carried out by comparative genomics and bioinformatics, have proven extremely powerful to obtain insight into the identity of specific genes that underlie differences and similarities across species. The central concept developed in this chapter is that important aspects of the functional differences between organisms derive not only from the differences in genetic components (which underlies comparative genomics) but also from dynamic, molecular (physical) interactions. Approaches that aim at identifying such network-based rather than component-based homologies between species we shall call Comparative Systems Biology. It will be illustrated by a number of examples from metabolic networks from prokaryotes, via yeast, to man. The potential for species comparisons, at the genome-scale using classical approaches and at the more detailed level of dynamic molecular networks will be illustrated. In our opinion, comparative systems biology, as a marriage between bioinformatics and systems biology, will offer new insights into the nature of organisms for the benefit of medicine, biotechnology, and drug design. As dynamic modeling is becoming more mainstream in cell biology, the potential of comparative systems biology will become more evident.
authors.affiliation: Systems BioInformatics, Center for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, The Netherlands.|Netherlands Institute Systems Biology (NISB), The Netherlands.|Kluyver Center for Genomics of Industrial Fermentation, The Netherlands.
authors.forename: Bas
authors.initials: B
authors.lastname: Teusink
authors.affiliation: Netherlands Institute Systems Biology (NISB), The Netherlands.|Molecular Cell Physiology, VU University Amsterdam, The Netherlands.|Manchester Centre for Integrative Systems Biology, University of Manchester, UK.
authors.forename: Hans V
authors.initials: HV
authors.lastname: Westerhoff
authors.affiliation: Systems BioInformatics, Center for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, The Netherlands.|Regulatory Networks Group, NISB, The Netherlands.|Life Sciences, Centre for Mathematics and Computer Science (CWI) Amsterdam, The Netherlands.
authors.forename: Frank J
authors.initials: FJ
authors.lastname: Bruggeman
mesh_terms: D000818:Animals; D001419:Bacteria / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology; D055808:Drug Discovery; D025461:Feedback, Physiological; D023281:Genomics; D006019:Glycolysis; D006801:Humans; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D013045:Species Specificity; D049490:Systems Biology / Q000639:trends