Computational approach for the prediction of ERF and DREB proteins in indica rice using support vector machine

Drought and salt stress are considered to be major impediments in rice production systems. To understand the genetics of tolerance to these abiotic stresses and develop drought/salt tolerant cultivars, genomic regions influencing yield and its response to water deficit have to be identified. A method for predicting two drought tolerant proteins viz. dehydration-responsive element binding proteins (DREB) and ethylene responsive factor (ERF) in the genome of indica rice has been described. The proposed method, ERFDREBSVMPRED, was developed using support vector machine and a prediction accuracy of 89% for DREB and 81% for ERF was achieved. The developed tool could predict DREB protein with 100% specificity at a 71% sensitivity rate and ERF protein with 100% specificity at a 60% sensitivity rate.