A computational genomics approach to identify cis-regulatory modules from chromatin immunoprecipitation microarray data—A case study using E2F1

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Figure 3.
Figure 3.

A graphical representation of the prediction rate (R) vs. Δ values (obtained from the CART results) for different groups of data. (Solid “*” line) Data for E2F1 on training data; (solid “x” line) data for non-E2F1 on training data; (broken “*” line) data for E2F1 on testing data after 10-fold cross validation; (broken “x” line) data for non-E2F1 on testing data after 10-fold cross validation. At a Δ of 270 bp, the prediction rates for E2F1 and non-E2F1 targets on both training and testing samples perform the best.

This Article

  1. Genome Res. 16: 1585-1595

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