AIF was identified as a marker protein for caspase independent apoptosis, In no

The predicted sensitivity value is then compared to its experimental value, the LOO error for each drug is the absolute value of the experimental sensitivity y minus the predicted sensitivity, i. e.y. The closer the predicted value is to the experimentally gener ated sensitivity, the lower the error for the withheld drug. Tables 1, 2, 3 and 4 provides the complete LOO error ARQ 197 代理店 tables and the average LOO error for each primary culture. The average LOO error over the 4 cell cultures is 0. 045 or 4. 5%. For the 10 fold cross validation error estimate, we divided the available drugs into 10 random sets of similar size and the testing is done on each fold while being trained on the remain ing 9 folds. This is repeated 10 times and average error calculated on the testing samples.<br><br> We again repeated this experiment 5 times and the average of those mean abso lute errors for the primary cell cultures are shown in Table 5. The detailed results of the 10 fold cross valida tion error analysis are included in Additional file 4. We note that both 10 fold CV and LOO AZD0530 臨床試験 estimates for all the cultures have errors less than 9%, which is extremely low, especially considering the still experimental nature of the drug screening process performed in the Keller laboratory and the available response of only 44 drugs with known target inhibition profile. To provide a measure of the overlap between drugs, we considered a similarity measure based on the EC50 of the drugs D1 and D2. Let the EC50 s of the drugs D1 and D2 be given by the n length vectors E1 and E2 where n denotes the number of drug targets.<br><br> The entries for the targets that are not inhibited by the drugs are set to 0. Let the vectors V1 Alvocidib 価格 and V2 represent the binarized targets of the drugs i. e. it has a value of 1 if the target is inhibited by the drug and a value of zero if the target is not inhibited by the drug. Then, we define the similarity measure as. Note that 1 and similarity between drugs with no overlapping targets is zero. If two drugs have 50% targets overlapping with same EC50 s, then the sim ilarity measure is 0. 5. The similarities between the drugs are shown in Additional file 5. Note that except two drugs Rapamycin and Temsirolimus that have a similar ity measure of 0. 989, all other drugs have significantly lower similarities with each other. The maximum simi larity between two different drugs is 0.<br><br> 169. This shows that any two drugs in the drug screen are not significantly overlapping and the prediction algorithm is still able to predict the response. The low error rate illustrates the accuracy and effec tiveness of this novel method of modeling and sensitivity prediction. Furthermore, these error rates are signifi cantly lower than those of any other sensitivity predic tion methodology we have found. Consistent with the analysis in, the sensitivity prediction rates improve dramatically when incorporating more information about drug protein interaction. To more effectively compare the results generated via the TIM framework with the results in, we also present the correlation coefficients between the predicted and experimental drug sensitivity values in Table 6.