Table 5

Statistical analysis of power-law parameters

Frequency of Pfam domains

Ligands per Pfam domain family

Ligands per target


xmin

10

81

210

alpha

2.07

1.71

2.15

Goodness of fit

0.5

0.42

0.42

vs_lognormal

yes (p = 5.1*10^-9)

yes/no (p = 0.48)

yes/no (p = 0.57)

vs_exponential

yes (p = 3.9*10^-3)

yes (p = 0.10)

yes (p = 8.5 *10^-8)

vs_weibull

yes (p = 2.1*10^-4)

Yes/no (p = 0.16)

no (p = 1.0*10^-3)

magnitude

~ 3

~ 3

~ 1

support for power-law

yes

yes

no


Parameters of the power-law functions fitted to the observed distributions of Pfam-A domain frequencies (left column), number of ligands associated with each Pfam-A domain (middle column) and number of ligands associated with individual targets (right column) are shown in columns 'xmin' and 'alpha'. 'Goodness of fit' indicates the p-Value calculated from a KS goodness of fit test. The rows vs_lognormal, vs_exponential, vs_weibull indicate outcomes of maximum-likelihood tests against alternative distributions. 'Yes' indicates significant support for a power-law distribution, 'no' indicates support for the alternative over a power-law. 'Magnitude' specifies the orders of magnitude in the distribution spanned by a power-law and 'support for power-law' is the summary outcome for each distribution.

Kruger et al. BMC Bioinformatics 2012 13(Suppl 17):S11   doi:10.1186/1471-2105-13-S17-S11

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