Caenorhabditis elegans
This is the metabolic network of the roundworm Caenorhabditis elegans.
Nodes are metabolites (e.g., proteins), and edges are interactions between
them. Since a metabolite can iteract with itself, the network contains loops.
The interactions are undirected. There may be multiple interactions between
any two metabolites.
Metadata
Statistics
Size  n =  453

Volume  m =  4,596

Unique edge count  m̿ =  2,040

Loop count  l =  22

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

4Tour count  T_{4} =  723,054

Maximum degree  d_{max} =  639

Average degree  d =  20.291 4

Fill  p =  0.019 838 4

Average edge multiplicity  m̃ =  2.252 94

Size of LCC  N =  453

Diameter  δ =  7

50Percentile effective diameter  δ_{0.5} =  2.081 97

90Percentile effective diameter  δ_{0.9} =  3.033 51

Median distance  δ_{M} =  3

Mean distance  δ_{m} =  2.641 74

Gini coefficient  G =  0.619 161

Relative edge distribution entropy  H_{er} =  0.898 868

Power law exponent  γ =  1.563 30

Tail power law exponent  γ_{t} =  2.621 00

Degree assortativity  ρ =  −0.225 821

Degree assortativity pvalue  p_{ρ} =  5.419 17 × 10^{−48}

Clustering coefficient  c =  0.124 436

Spectral norm  α =  162.930

Algebraic connectivity  a =  0.264 802

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.432 48

Nonbipartivity  b_{A} =  0.301 910

Normalized nonbipartivity  b_{N} =  0.200 552

Algebraic nonbipartivity  χ =  0.293 559

Spectral bipartite frustration  b_{K} =  0.008 148 41

Controllability  C =  8

Relative controllability  C_{r} =  0.040 000 0

Plots
Matrix decompositions plots
Downloads
References
[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.
