Recursive partitioning model

In any recursive partitioning technique, power drops dramatically as we split our data into smaller and smaller groups so that, except in huge samples, the final model selected understates the actual number of useful predictors. By giving all significant predictors the opportunity to be used for splitting, RRP makes it easy to find a more complete set of relevant variables. 

A number of reports also describe the prediction of mechanism-based inhibition (MBI) [17,18]. In this type of model, MBI is determined in part by spectral shift and inactivation kinetics. Jones et al. applied computational pharmacophores, recursive partitioning and logistic regression in attempts to predict metabolic intermediate complex (MIC) formation from structural inputs [17]. The development of models that accurately predict MIC formation will provide another tool to help reduce the overall risk of DDI [19]. 

Glick, M. et al. 2006. Enrichment of high-throughput screening data with increasing levels of noise using support vector machines, recursive partitioning, and Laplacian-modified naive Bayesian classifiers. J. Chem. Inf. Model. 46, 193-200. 

Nilakantan R, Nunn DS, Greenblatt L, Walker G, Haraki K, et al. A family of ring system-based structural fragments for use in structure-activity studies Database mining and recursive partitioning. J Chem Inf Model 2006 46(3) 1069-77. 

Recursive partitioning has successfully been used to develop models for various ADM ET properties, see Ref. [80], as well as for the elucidation of toxicological modes of action [103]. 

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