Bacterial adaptation during chronic infection revealed by independent component analysis of transcriptomic data.

ABSTRACT:

Background

Bacteria employ a variety of adaptation strategies during the course of chronic infections. Understanding bacterial adaptation can facilitate the identification of novel drug targets for better treatment of infectious diseases. Transcriptome profiling is a comprehensive and high-throughput approach for characterization of bacterial clinical isolates from infections. However, exploitation of the complex, noisy and high-dimensional transcriptomic dataset is difficult and often hindered by low statistical power.

Results

In this study, we have applied two kinds of unsupervised analysis methods, principle component analysis (PCA) and independent component analysis (ICA), to extract and characterize the most informative features from transcriptomic dataset generated fro

SUBMITTER: Yang L 

PROVIDER: S-EPMC3224102 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature