Philosophiae Doctor - PhD / Drought is the most complex phenomenon that remained to be a potential and historic challenge to human welfare. It affects plant productivity by eliciting perturbations related to a pathway that controls a normal, functionally intact biological process of the plant. Sorghum (Sorghum bicolor (L.) Moench), a drought adapted model cereal grass is a potential target in the modem agricultural research towards understanding the molecular and cellular basis of drought tolerance. This study reports on the genomic and proteomic findings of drought tolerance in sorghum combining the results from in silica and experimental analysis. Pipeline that includes mapping expression data from 92 normalized cDNAs to genomic loci were used to identify drought tolerant genes. Integrative analysis was carried out using sequence similarity search, metabolic pathway, gene expression profiling and orthology relation to investigate genes of interest. Gene structure prediction was conducted using combination of ab initio and extrinsic evidence-driven information employing multi-criteria sources to improve accuracy. Gene ontology was used to cross-validate and to functionally assign and enrich genes. An integrated approach that subtly combines functional ontology based semantic data with expression profiling and biological networks was employed to analyse gene association with plant phenotypes and to identify and genetically dissect complex drought tolerance in sorghum. The gramene database was used to identify genes with direct or indirect association to drought related ontology terms in sorghum. Where direct association for sorghum genes were not available, genes were captured using Ensemble Biomart by transitive association based on the putative functions of sorghum orthologs in closely related species. Ontology mapping represented a direct or transitive association of genes to multiple drought related ontology terms based on sorghum specific genes or orthologs in related species. Correlation of genes to enriched gene ontology (GO)-terms (p-value < 0.05) related to the whole-plant structure was used to determine the extent of gene-phynotype association across-species and environmental stresses.