کنگره بین المللی زیست فناوری گیاهان دارویی و قارچ های کوهی

صفحه اصلی / چهارمین کنگره بین المللی و پنجمین همایش ملی زیست فناوری گیاهان دارویی و قارچ های کوهی

The importance of generating and applying big data and establishing databases specific to medicinal plants based on OMICS approaches

نویسندگان :

Seyed Alireza Salami¹

1- University of Tehran

کلمات کلیدی :

Integrated OMICS،Systems biology،Gene network،Genome،Big data

چکیده :

Medicinal herbs have been used for thousands of years and have great impacts on people life-style from birth to the death. They come to our table as food, bioenergetics drinks, and medicine. The consumption of medicinal herbs has increased in the last decades due to their beneficial health effects related to a wide range of diverse secondary metabolites. However, in comparison with other crops, there is less OMICS information available for medicinal plants yet. Such an inadequate knowledge resulted in a big gap in their pre-breeding and breeding programs, their mode of action, biosynthesis pathways, potential adverse reactions, and interactions with existing pharmaceuticals and functional foods. Therefore, generating and applying big data and establishing databases specific to medicinal plants will have a huge revolutionary impact on medicinal herbs. During last decade several new approaches have been developed particularly based on OMICS approaches, led to deeper understanding of genome context, genes and related biological processes in medicinal plants, and their proteome and metabolome profiles. Consequently, the enormous amount of data generated need to be archived in databases, processed and analyzed. Sequencing the whole genome of some medicinal plants just recently has provided a spark of light to answer the questions and ambiguities more accurately. These genomic sequences can be integrated with transcriptome, proteome and metabolome data to unravel the mysteries of biological process in medicinal herbs. Nevertheless, to use such big data we have to think big and multidisciplinary. For big data management and analysis as well, we have to do paradigm shift in concepts, skills and tools. In this case, frameworks such as HADOOP, and tools such as MapReduce, Java, and Pig further improve storing and processing efficiency and the accuracy and performance of our modules. Eventually, we have to consider all challenges like data privacy, data security, and data accessibility to fulfill all related necessary infrastructures towards establishment a database.