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. 2010 Nov 30;5(11):e13876. doi: 10.1371/journal.pone.0013876

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Schröder et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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Each dot indicates the predicted and known PFM similarity of all TF-pairs in the test dataset. The -axis gives the sequence based SVR-based PFM similarity prediction and the -axis gives the similarity of their known PFMs. Thereby, for each structural superclass the best SVR model from the training dataset was used for the predictions. The Pearson correlation-coefficients are as follows: basic domain: 0.77, zinc finger: 0.80, helix-turn-helix: 0.77 and beta-scaffold: 0.64.

Inline graphic — Each dot indicates the predicted and known PFM similarity of all TF-pairs in the test dataset. The -axis gives the sequence based SVR-based PFM similarity prediction and the -axis gives the similarity of their known PFMs. Thereby, for each structural superclass the best SVR model from the training dataset was used for the predictions. The Pearson correlation-coefficients are as follows: basic domain: 0.77, zinc finger: 0.80, helix-turn-helix: 0.77 and beta-scaffold: 0.64.