Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Functional cartography of complex metabolic networks


High-throughput techniques are leading to an explosive growth in the size of biological databases and creating the opportunity to revolutionize our understanding of life and disease. Interpretation of these data remains, however, a major scientific challenge. Here, we propose a methodology that enables us to extract and display information contained in complex networks1,2,3. Specifically, we demonstrate that we can find functional modules4,5 in complex networks, and classify nodes into universal roles according to their pattern of intra- and inter-module connections. The method thus yields a ‘cartographic representation’ of complex networks. Metabolic networks6,7,8 are among the most challenging biological networks and, arguably, the ones with most potential for immediate applicability9. We use our method to analyse the metabolic networks of twelve organisms from three different superkingdoms. We find that, typically, 80% of the nodes are only connected to other nodes within their respective modules, and that nodes with different roles are affected by different evolutionary constraints and pressures. Remarkably, we find that metabolites that participate in only a few reactions but that connect different modules are more conserved than hubs whose links are mostly within a single module.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Performance of module identification methods.
Figure 2: Roles and regions in the zP parameter space.
Figure 3: Cartographic representation of the metabolic network of E. coli.
Figure 4: Roles of metabolites and inter-species conservation.


  1. 1

    Amaral, L. A. N., Scala, A., Barthelémy, M. & Stanley, H. E. Classes of small-world networks. Proc. Natl Acad. Sci. USA 97, 11149–11152 (2000)

    ADS  CAS  Article  Google Scholar 

  2. 2

    Albert, R. & Barabási, A.-L. Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)

    ADS  MathSciNet  Article  Google Scholar 

  3. 3

    Amaral, L. A. N. & Ottino, J. Complex networks: Augmenting the framework for the study of complex systems. Eur. Phys. J. B 38, 147–162 (2004)

    ADS  CAS  Article  Google Scholar 

  4. 4

    Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. From molecular to modular biology. Nature 402 (Suppl.), C47–C52 (1999)

    CAS  Article  Google Scholar 

  5. 5

    Girvan, M. & Newman, M. E. J. Community structure in social and biological networks. Proc. Natl Acad. Sci. USA 99, 7821–7826 (2002)

    ADS  MathSciNet  CAS  Article  Google Scholar 

  6. 6

    Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabási, A. L. The large-scale organization of metabolic networks. Nature 407, 651–654 (2000)

    ADS  CAS  Article  Google Scholar 

  7. 7

    Wagner, A. & Fell, D. A. The small world inside large metabolic networks. Proc. R. Soc. Lond. B 268, 1803–1810 (2001)

    CAS  Article  Google Scholar 

  8. 8

    Ma, H. & Zeng, A.-P. Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms. Bioinformatics 19, 270–277 (2003)

    CAS  Article  Google Scholar 

  9. 9

    Hatzimanikatis, V., Li, C., Ionita, J. A. & Broadbelt, L. Metabolic networks: enzyme function and metabolite structure. Curr. Opin. Struct. Biol. 14, 300–306 (2004)

    CAS  Article  Google Scholar 

  10. 10

    Guimerà, R., Danon, L., Díaz-Guilera, A., Giralt, F. & Arenas, A. Self-similar community structure in a network of human interactions. Phys. Rev. E 68, no. 065103 (2003)

    ADS  Article  Google Scholar 

  11. 11

    Newman, M. E. J. & Girvan, M. Finding and evaluating community structure in networks. Phys. Rev. E 69, no. 026113 (2004)

    ADS  Google Scholar 

  12. 12

    Arenas, A., Danon, L., Díaz-Guilera, A., Gleiser, P. M. & Guimerà, R. Community analysis in social networks. Eur. Phys. J. B 38, 373–380 (2004)

    ADS  CAS  Article  Google Scholar 

  13. 13

    Krause, A. E., Frank, K. A., Mason, D. M., Ulanowicz, R. E. & Taylor, W. W. Compartments revealed in food-web structure. Nature 426, 282–285 (2003)

    ADS  CAS  Article  Google Scholar 

  14. 14

    Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N. & Barabási, A.-L. Hierarchical organization of modularity in metabolic networks. Science 297, 1551–1555 (2002)

    ADS  CAS  Article  Google Scholar 

  15. 15

    Holme, P. & Huss, M. Subnetwork hierarchies of biochemical pathways. Bioinformatics 19, 532–538 (2003)

    CAS  Article  Google Scholar 

  16. 16

    Papin, J. A., Reed, J. L. & Palsson, B. O. Hierarchical thinking in network biology: the unbiased modularization of biochemical networks. Trends Biochem. Sci. 29, 641–647 (2004)

    CAS  Article  Google Scholar 

  17. 17

    Eriksen, K. A., Simonsen, I., Maslov, S. & Sneppen, K. Modularity and extreme edges of the Internet. Phys. Rev. Lett. 90, no. 148701 (2003)

    ADS  Article  Google Scholar 

  18. 18

    Newman, M. E. J. Fast algorithm for detecting community structure in networks. Phys. Rev. E 69, no. 066133 (2004)

    ADS  Google Scholar 

  19. 19

    Radicchi, F., Castellano, C., Cecconi, F., Loreto, V. & Parisi, D. Defining and identifying communities in networks. Proc. Natl Acad. Sci. USA 101, 2658–2663 (2004)

    ADS  CAS  Article  Google Scholar 

  20. 20

    Donetti, L. & Muñoz, M. A. Detecting network communities: A new systematic and efficient algorithm. J. Stat. Mech. Theor. Exp., P10012 (2004)

  21. 21

    Guimerà, R., Sales-Pardo, M. & Amaral, L. A. N. Modularity from fluctuations in random graphs and complex networks. Phys. Rev. E 70, no. 025101 (2004)

    ADS  Article  Google Scholar 

  22. 22

    Kirkpatrick, S., Gelatt, C. D. & Vecchi, M. P. Optimization by simulated annealing. Science 220, 671–680 (1983)

    ADS  MathSciNet  CAS  Article  Google Scholar 

  23. 23

    Wasserman, S. & Faust, K. Social Network Analysis Ch. 12, 4 (Cambridge Univ. Press, Cambridge, 1994)

    Google Scholar 

  24. 24

    Guimerà, R. & Amaral, L. A. N. Cartography of complex networks: Modules and universal roles. J. Stat. Mech. Theor. Exp. P02001 (2005)

  25. 25

    Rives, A. W. & Galitski, T. Modular organization of cellular networks. Proc. Natl Acad. Sci. USA 100, 1128–1133 (2003)

    ADS  CAS  Article  Google Scholar 

  26. 26

    Han, J.-D. J. et al. Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature 430, 88–93 (2004)

    ADS  CAS  Article  Google Scholar 

  27. 27

    Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000)

    CAS  Article  Google Scholar 

  28. 28

    Schuster, S., Fell, D. A. & Dandekar, T. A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nature Biotechnol. 18, 326–332 (2000)

    CAS  Article  Google Scholar 

  29. 29

    Schuster, S., Pfeiffer, T., Moldenhauer, F., Koch, I. & Dandekar, T. Exploring the pathway structure of metabolism: decomposition into subnetworks and application to Microplasma pneumoniae . Bioinformatics 18, 351–361 (2002)

    CAS  Article  Google Scholar 

  30. 30

    Jeong, H., Mason, S. P., Barabási, A.-L. & Oltvai, Z. N. Lethality and centrality in protein networks. Nature 411, 41–42 (2001)

    ADS  CAS  Article  Google Scholar 

Download references


We thank L. Broadbelt, V. Hatzimanikatis, A. A. Moreira, E. T. Papoutsakis, M. Sales-Pardo and D. B. Stouffer for discussions and suggestions, and H. Ma and A. P. Zeng for providing us with their metabolic networks' database. R.G. thanks the Fulbright Program and the Spanish Ministry of Education, Culture & Sports. L.A.N.A. acknowledges the support of a Searle Leadership Fund Award and of a NIH/NIGMS K-25 award.

Author information



Corresponding author

Correspondence to Luís A. Nunes Amaral.

Ethics declarations

Competing interests

The authors declare that they have no competing financial interests.

Supplementary information

Supplementary Discussion

Additional information on role definition, application of the method to metabolic networks, and discussion of the results. This file contains 13 figures (S1-S13). (PDF 1699 kb)

Supplementary Table 1

Module description (including metabolite list) for the 12 organisms as obtained from the MZ database. (XLS 60 kb)

Supplementary Table 2 (module)

Module description (including metabolite list) for the 12 organisms as obtained from the KEGG database. (XLS 123 kb)

Supplementary Table 2 (role)

Role description (including metabolite list) for the 12 organisms as obtained from the KEGG database. (XLS 112 kb)

Supplementary Table 3

Role description (including metabolite list) for the 12 organisms as obtained from the MZ database. (XLS 72 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Guimerà, R., Nunes Amaral, L. Functional cartography of complex metabolic networks. Nature 433, 895–900 (2005).

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing