Novel algorithms reveal streptococcal transcriptomes and clues about undefined genes.

Bacteria-host interactions are dynamic processes, and understanding transcriptional responses that directly or indirectly regulate the expression of genes involved in initial infection stages would illuminate the molecular events that result in host colonization. We used oligonucleotide microarrays to monitor (in vitro) differential gene expression in group A streptococci during pharyngeal cell adherence, the first overt infection stage. We present neighbor clustering, a new computational method for further analyzing bacterial microarray data that combines two informative characteristics of bacterial genes that share common function or regulation: (1) similar gene expression profiles (i.

Single nucleotide polymorphism seeking long term association with complex disease.

Successful investigation of common diseases requires advances in our understanding of the organization of the genome. Linkage disequilibrium provides a theoretical basis for performing candidate gene or whole-genome association studies to analyze complex disease. However, to constructively interrogate SNPs for these studies, technologies with sufficient throughput and sensitivity are required.