Arabidopsis thaliana is a popular species for understanding the molecular biology of many plants traits, salinity being one. The most up-to-date version of the Arabidopsis thaliana genome sequence database is maintained by the Arabidopsis Information Resource (TAIR). Several stress associated genes have already been evaluated in greater details and validated through wet-lab experimentations around the world. Though, Arabidopsis being a glycophyte and thus having limitations for being used in high salinity experiments, it is none-the-less an ideal plant to probe for hitherto undiscovered genes that may have some indications of role in the mechanism of salt tolerance. Such putative genes remain hidden until discovered through various ways. The authors here report a new approach which is being named –'in silico cascade approach' for identification of putative genes. The approach utilizes the gene expression information from DNA microarrays available in public domain. The information is first filtered through a set of bioinformatics tools and then in a cascade fashion, the output from one tool is subjected to another set of tools to narrow down upon data that points towards a putative gene, not discovered before. The approach uses public domain datasets from 'Gene Expression Omnibus' (GEO), 'Array Express' and 'Plant Expression Database' (PLEXDb). The filtered data is subjected to analysis using tools like 'Webarray' and 'Genevestigator' and subjectsd to analysis using 'GLaMAa' for ranking the unknown genes using PERL coding, 'VirtulPlant Server' for generating a graphical hypothesis and 'AthaMap' for finding transcription factor binding sites. Using this unique in silico cascade approach, a total of nine putative genes with role in salt stress management have so far been predicted using Genevestigator's co-expression analysis tool through Pearson correlation coefficient as the measure of similarity between genes, both for identifying co-expressed genes as well as to define the pair wise correlation between genes.