Advanced tissue analysis using a combined histomorphometric and gene expression profiling method

We report on development of a new type of tissue analysis that facilitates a comprehensive method to characterize tissues and simultaneously identifies significant genes, based on the combination of different statistical approaches using co-variants such as quantitative microscopical tissue data. The introduction of tissue imaging into bioinformatics relies on a computer assisted histomorphometry, which enables tissue imaging to be executed in a fully automated, high-throughput fashion with quantitative analytical capabilities. As cells and tissues are centrally located in the biological hierarchy of function, improvements in the ability to obtain more quantitative information about tissue structure are critical to elucidate upstream functional effects of gene and protein expression. Furthermore, a detailed quantitative description of tissues may be expected to improve diagnosis and the understanding of structure and function of larger tissue constructs and organs in normal and disease states. Particular methods are described here that correlate gene expression to tissue structural data, essentially linking a bottom-up and top-down methodology important for improvement of diagnosis and discovery informatics.