Caenorhabditis elegans (metabolic)

This is the metabolic network of Caenorhabditis elegans.


Internal namedimacs10-celegans_metabolic
NameCaenorhabditis elegans (metabolic)
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Metabolic network
Node meaningMetabolite
Edge meaningInteraction
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
LoopsDoes not contain loops
Completeness Is incomplete


Size n =453
Volume m =2,025
Loop count l =0
Wedge count s =79,173
Claw count z =3,352,172
Cross count x =153,983,040
Triangle count t =3,284
Square count q =50,289
4-Tour count T4 =723,054
Maximum degree dmax =237
Average degree d =8.940 40
Fill p =0.019 779 6
Size of LCC N =453
Diameter δ =7
50-Percentile effective diameter δ0.5 =2.143 50
90-Percentile effective diameter δ0.9 =3.169 35
Median distance δM =3
Mean distance δm =2.676 27
Gini coefficient G =0.494 803
Relative edge distribution entropy Her =0.898 264
Power law exponent γ =1.565 69
Tail power law exponent γt =2.631 00
Degree assortativity ρ =−0.225 821
Degree assortativity p-value pρ =5.419 17 × 10−48
Clustering coefficient c =0.124 436
Spectral norm α =26.308 5
Algebraic connectivity a =0.258 000
Non-bipartivity bA =0.429 332
Normalized non-bipartivity bN =0.200 551
Algebraic non-bipartivity χ =0.293 557
Spectral bipartite frustration bK =0.008 208 72


Fruchterman–Reingold graph drawing

Degree distribution

Cumulative degree distribution

Lorenz curve

Spectral distribution of the adjacency matrix

Spectral distribution of the normalized adjacency matrix

Spectral distribution of the Laplacian

Spectral graph drawing based on the adjacency matrix

Spectral graph drawing based on the Laplacian

Spectral graph drawing based on the normalized adjacency matrix

Degree assortativity

Zipf plot

Hop distribution

Double Laplacian graph drawing

Delaunay graph drawing

Clustering coefficient distribution

Average neighbor degree distribution


Matrix decompositions plots



[1] Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]
[2] Jordi Duch and Alex Arenas. Community detection in complex networks using extremal optimization. Phys. Rev. E, 72(2):027104, 2005.