Expanding the understanding of biases in development of clinical-grade molecular signatures: a case study in acute respiratory viral infections.

ABSTRACT:

Background

The promise of modern personalized medicine is to use molecular and clinical information to better diagnose, manage, and treat disease, on an individual patient basis. These functions are predominantly enabled by molecular signatures, which are computational models for predicting phenotypes and other responses of interest from high-throughput assay data. Data-analytics is a central component of molecular signature development and can jeopardize the entire process if conducted incorrectly. While exploratory data analysis may tolerate suboptimal protocols, clinical-grade molecular signatures are subject to vastly stricter requirements. Closing the gap between standards for exploratory versus clinically successful molecular signatures entails a thorough understanding of pos

SUBMITTER: Lytkin NI 

PROVIDER: S-EPMC3105991 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature