Table 6

Classification Performance on the Protein-DNA Interaction Site Prediction.

w = f = 3

w = f = 7

w = f = 11


ROC

F1

ROC

F1

ROC

F1


0.756

0.463

0.758*

0.469

0.748

0.452

0.753

0.465

0.754

0.462

0.759

0.466

0.754

0.466

0.756

0.468

0.763

0.468


The numbers in bold show the best models for a fixed w parameter, as measured by ROC. , and represent the PSI-BLAST profile and YASSPP scoring matrices, respectively. soe, rbf, and lin represent the three different kernels studied using the as the base kernel. * denotes the best classification results in the sub-tables, and ** denotes the best classification results achieved on this dataset. For the best model we report a Q2 accuracy of 83.0% with an se rate of 0.34.

Rangwala et al. BMC Bioinformatics 2009 10:439   doi:10.1186/1471-2105-10-439

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