ABSTRACT
Plant productivities are hugely affected by adverse’?) from several research fields are of real concern while analyzing via conventional strategies. This is where introducing computational biology will hopefully be extremely beneficial. Several machine learning methods are not only available but also are used on a regular basis for analyzing such data with larger multitudes and dimensions in biological research. Those analyses have been proved useful from modeling system to understanding the ‘big pictures’. Usages of databases, genetic ontology modeling of the structures of molecules etc. have significantly given input to the empirical studies. This chapter is trying to provide a review of how different computational modeling and in silico approaches have been shown to be helpful for studying stress responses of plants. The author is highly enthusiastic that this study might be proven quite enriching for new-age plant stress biologists as well as for rigorous and experienced empirical researchers.
