In order to assess global changes in gene expression patterns in stress-induced tissues, we conducted large-scale analysis of expressed sequence tags (ESTs) in common wheat. Twenty-one cDNA libraries derived from stress-induced tissues, such as callus, as well as liquid cultures and abiotic stress conditions (temperature treatment, desiccation, photoperiod, moisture and ABA) were constructed. Several thousand colonies were randomly selected from each of these 21 cDNA libraries and sequenced from both the 5' and 3' ends. By computing abundantly expressed ESTs, correlated expression patterns of genes across the tissues were monitored. Furthermore, the relationships between gene expression profiles among the stress-induced tissues were inferred from the gene expression patterns. Multi-dimensional analysis of EST data is analogous to microarray experiments. As an example, genes specifically induced and/or suppressed by cold acclimation and heat-shock treatments were selected in silico. Four hundred and ninety genes showing fivefold induction or 218 genes for suppression in comparison to the control expression level were selected. These selected genes were annotated with the BLAST search. Furthermore, gene ontology was conducted for these genes with the InterPro search. Because genes regulated in response to temperature treatment were successfully selected, this method can be applied to other stress-treated tissues. Then, the method was applied to screen genes in response to abiotic stresses such as drought and ABA treatments. In silico selection of screened genes from virtual display should provide a powerful tool for functional plant genomics.