Open Access Highly Accessed Research article

Scaling properties of protein family phylogenies

Alejandro Herrada1*, Víctor M Eguíluz1, Emilio Hernández-García1 and Carlos M Duarte23

Author Affiliations

1 Instituto de Física Interdisciplinar y Sistemas Complejos, IFISC (CSIC-UIB), Campus Universitat de les Illes Balears, E-07122 Palma de Mallorca, Spain

2 Instituto Mediterráneo de Estudios Avanzados, IMEDEA (CSIC-UIB), C/Miquel Marqués 21, E-07190 Esporles, Spain

3 Oceans Institute, University of Western Australia, 35 Stirling Highway, Crawley 6009, Australia

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BMC Evolutionary Biology 2011, 11:155  doi:10.1186/1471-2148-11-155

Published: 6 June 2011

Additional files

Additional file 1:

Branch size and mean depth examples. The values of the branch size, A and of the mean depth, d, are shown (in brackets, as (A,d)) at each node of a fully balanced 15-tip phylogenetic tree (a), a fully imbalanced 15-tip phylogenetic tree (b), a 15-tip subtree of a real phylogenetic tree.

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Additional file 2:

Power-law vs. logarithmic scaling of the depth with tree size. We compare the local exponents of the possible scaling laws of the depth with tree size for PANDIT. For sizes larger than 300 fluctuations make estimations unreliable. Filled squares: For the power-law scaling d ~ Aη the local exponent at bin i is calculated as ηi = Δi ln di ln A, where Δi indicates the difference between two consecutive bins, for instance Δi ln d = ln d(i + 1) ln d(i). Empty diamonds: For the log scaling d ~ (ln A)β the local exponent at bin i is calculated as βi = Δi ln di ln ln A. Constant values of the local exponents, or values approaching a given value as sizes increase, indicate appropriateness of the corresponding scaling laws to describe the data. For the power-law scaling, the exponent is around η ≃ 0.5 and slightly decays for larger trees. For the logarithmic scaling, the exponent approaches 2 as larger trees are considered, indicating d ~ (ln A)2. The results indicate comparable quality of fit for both laws at the reliable range. Note that the simpler logarithmic law, β = 1, is not supported by the available data.

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Additional file 3:

Standard deviation of the evolvability model. Values of the standard error (SE) of the results from simulations of the evolvability model with respect to the PANDIT dataset, for values of p between [0.21 - 0.27]. A value p = 0.24 minimizes the error.

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