Bioinformatics Tools and Big Data Analytics for Understanding Agricultural Microbial Ecosystems

Applied Microbiology (Switzerland) · Published 2026-06-28 · DOI 10.3390/applmicrobiol6070073

Free full text

Authors (5)

Madan L. Verma, Meenu Thakur, Prachi Arora, Prince Sharma, Sarita Devi

Abstract

Microbial diversity and sustainable agriculture are key players for the mutual harmony of the nature/agriculture ecosystem that align with the Sustainable Development Goals (SDGs). However, to harness their best potential, it is necessary to understand the complex interactions between microbial communities and plants. This has become feasible with the intervention of advanced multiomics techniques including genomics, metagenomics, transcriptomics, proteomics, metabolomics, etc. With the advent of next-generation technologies, production of biological data at a cost-effective expense has escalated rapidly. Thus, it is feasible for all researchers to explore these advanced technologies for a better understanding of how to harness the full potential of microbial diversity toward sustainable agriculture. The growth of biological databases, particularly microbial databases, and interphasic tools are bound to the rapid growth of bioinformatics domains. Additionally, bioinformatics provides the direction for better understanding of the interaction of the microbe–plant system. Keeping in view the expansion of escalated biological datasets, the role of big data analytics is vital to understand the interplay of the diverse datasets along with the growing biological databases. The relevant case studies employing big data analytics in sustainable agriculture have been discussed. This will help to make better decisions toward the productivity of sustainable agriculture. This review is an attempt to showcase the recent growth of bioinformatics databases and the role of big data analytics in achieving sustainable agriculture.

Abstract from DOAJ. Public domain (CC0 1.0).

Read the article at the publisher →

Publication details

Year
2026

Citation

Verma, M., Thakur, M., Arora, P., et al. (2026). Bioinformatics Tools and Big Data Analytics for Understanding Agricultural Microbial Ecosystems. Applied Microbiology (Switzerland). https://doi.org/10.3390/applmicrobiol6070073

Related articles