MULTIDIMENSIONAL INTEGRATIVE EXPRESSION PROFILING FOR SAMPLE CLASSIFICATION

摘要

An organized knowledge-supervised approach-Multidimensional Integrative eXpression Profiling (MIXP)-can not only improve sample classification accuracy by serving as a feature transformation approach, but also help in the discovery of groups of crucial molecular entities that have been too weak to detect individually through preexisting methods. Functionally related molecules that are individually expressed with low differentials, have often been considered as noise and ignored in traditional studies, but through the MIXP approach, they can be readily identified by virtue of their coordinate expression.