Integrating Biological Covariates into Gene Expression-Based Predictors of Radiation Sensitivity

Figure 1

Investigation of building predictors for radiation sensitivity in 48 cell lines. (a) Classification accuracy of radiation sensitivity predictor built from 48 cell lines, using different numbers of features in the regression model. (b) Classification accuracy of radiation sensitivity predictor built from 48 cell lines, using different types of normalization. MAS5.0 and MAS4.0 algorithms generated the most accurate predictors. (c) Classification accuracy of radiation sensitivity predictor built from 48 cell lines, using different types of classification algorithms, including linear regression, least median, and SMO.

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