In Silico Expression Analysis.

Information on the specificity of cis-sequences enables the design of functional synthetic plant promoters that are responsive to specific stresses. Potential cis-sequences may be experimentally tested, however, correlation of genomic sequence with gene expression data enables an in silico expression analysis approach to bioinformatically assess the stress specificity of candidate cis-sequences prior to experimental verification. The present chapter demonstrates an example for the in silico validation of a potential cis-regulatory sequence responsive to cold stress.

'In silico expression analysis', a novel PathoPlant web tool to identify abiotic and biotic stress conditions associated with specific cis-regulatory sequences.

Using bioinformatics, putative cis-regulatory sequences can be easily identified using pattern recognition programs on promoters of specific gene sets. The abundance of predicted cis-sequences is a major challenge to associate these sequences with a possible function in gene expression regulation. To identify a possible function of the predicted cis-sequences, a novel web tool designated 'in silico expression analysis' was developed that correlates submitted cis-sequences with gene expression data from Arabidopsis thaliana.

'MicroRNA Targets', a new AthaMap web-tool for genome-wide identification of miRNA targets in Arabidopsis thaliana.

Background: The AthaMap database generates a genome-wide map for putative transcription factor binding sites for A. thaliana. When analyzing transcriptional regulation using AthaMap it may be important to learn which genes are also post-transcriptionally regulated by inhibitory RNAs.