Here, effec tiveness is determined by the desired level of sensitivity before which a treatment will not be considered satis factory. The two Boolean relationships are reflected in the 2 rules presented previously. By extension, a NOT relationship would http://www.selleckchem.com/products/kpt-330.html capture the behavior of tumor sup pressor targets, this behavior is not directly considered in this paper. Another possibility is XOR and we do not consider it in the current formulation due to the absence of sufficient evidence for existence of such behavior at the kinase target inhibition level. Thus, our underlying network consists of a Boolean equation with numerous terms. To construct the minimal Boolean equation that describes the underlying network, we utilize the concept of TIM presented Dacomitinib in the previous section.

Note that generation of the complete TIM would require 2n ? c 2n inferences. The inferences are of negligible computation cost, but for a reasonable n, the number of necessary inferences can become prohibitive as the TIM is exponential in size. We assume that generat ing the complete TIM is computationally infeasible within the desired time frame to develop treatment strategies for new patients. Thus, we fix a maximum size for the number of targets in each target combination to limit the number of required inference steps. Let this maximum number of targets considered be M. We then consider all non experimental sensitivity com binations with fewer than M 1 targets. As we want to generate a Boolean equation, we have to binarize the resulting inferred sensitivities to test whether or not a tar get combination is effective.

We denote the binarization threshold for inferred sensitivity values by. Asi 1, an effective combination becomes more restric tive, and the resulting boolean equations will have fewer effective terms. There is an equivalent term for target combinations with experimental sensitivity, denotede. We begin with the target combinations with experimen tal sensitivities. For converting the target combinations with experimental sensitivity, we binarize those target combinations, regardless of the number of targets, where the sensitivity is greater thane. The terms that represent a successful treatment are added to the Boolean equation. Furthermore, the terms that have sufficient sensitivity can be verified against the drug representation data to reduce the error.

To find the terms of the network Boolean equation, we begin with all possible target combinations of http://www.selleckchem.com/products/Imatinib-Mesylate.html size 1. If the sensitivity of these single targets are suf ficient relative toi ande, the target is binarized, any further addition of targets will only improve the sensitivity as per rule 3. Thus, we can consider this target completed with respect to the equation, as we have created the mini mal term in the equation for the target.