Big Data Analysis of Medicinal Plants

Medicinal plants are a rich source of specialised metabolites with significant pharmacological characteristics. Limitations in the availability of plant genomics resources hindered the complete investigation of the biosynthesis routes of these compounds. However, plant biologists have recently identified the biosynthetic pathways for significant plant-based medicinal compounds because of advancements in high-throughput, large-scale analytical technologies. The elucidation of the biosynthesis pathways for various bioactive metabolites of plant origin has been made possible by the decreased cost of producing big datasets and the development of computer tools for their analysis and integration. These findings have motivated the development of microbial production systems to manufacture bioactive metabolites from plants as an alternative sustainable supply of crucial molecules for medicine. Understanding the biosynthesis of specialist metabolites is essential to finding or creating trustworthy sources in the future since the demand for therapeutic chemicals is rising along with the global population. Here, we examine the contribution of big data and how they were integrated into our knowledge of the biosynthetic processes that give rise to bioactive metabolites. We discuss the various methods of producing the biological datasets and their integration to derive physiologically pertinent information as well as the use of these datasets in creating and reconstructing metabolic models.