RANDOM FOREST MODELING OF CELLULAR PHENOTYPES

摘要

A method of generating classification models to predict biological activity of a population of cells is provided. In certain embodiments, the method involves a) receiving a training set having values for independent and dependent variables associated with populations of cells; b) clustering the training set; c) randomly selecting, with replacement, clusters of cell populations to construct multiple bootstrap samples of the size of the training set; and d) generating a random forest model for each bootstrap sample, wherein the ensemble of random forest models may be used to classify the test population. Also provided are methods of predicting whether a test population of cells exhibits a pathology or biological activity. In certain embodiments, the methods involve applying data about the test population of cells to an ensemble of random forest models. The prediction may be made by aggregating the predictions of the random forest models in the ensemble.