Relational biomarkers that distinguish diseases and disorders from controls and uses thereof to predict pathophysiological outcomes

Abstract

Methods for modeling system behavior and discovering relational biomarkers that distinguish a disease/disorder sample from a control sample. The methods generally include modeling a mathematical relationship between a pattern of a first biological material and the pattern(s) on one or more other biological samples for samples from each of a plurality of subjects having the disease/disorder to determine a case relational biomarker, and for samples from each of a plurality of subjects absent the disease/disorder to determine a control or noncase relational biomarker. These case noncase biomarkers, or discriminators, may be used to classify an unknown sample. Ensembles of discriminators may be generated by modeling the relationships among different combinations of biological materials. Moreover, ensembles of discriminators for various diseases or disorders, i.e., multiclass classifiers, may be generated by modeling the relationships among material from subjects who have or will develop additional diseases or disorders.

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