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Predictive Modeling of Anti-Cancer Drug Sensitivity from Genetic Characterizations
1Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USA.
Abstract:
Accurately predicting sensitivity of tumor cells to anti-cancer drugs based on genetic characterizations is a significant challenge for personalized cancer therapy. This chapter provides a computational procedure to design predictive models from individual genomic characterizations and combine them to arrive at an integrated predictive model. Integrated modeling employs the complementary information from heterogeneous genetic characterizations to improve the prediction error as well as lowering the error confidence interval.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

