Artificial Intelligence in Microbiological Research: Methods, Applications and Implications

Year : 2026 | Volume : 16 | 02 | Page :
    By

    V. Basil Hans,

  1. Associate Professor, Department of Economics, Christ (Deemed to be University) Bangalore, Karnataka, India

Abstract

Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than conventional analytical methods, allowing researchers to identify meaningful patterns and generate accurate predictions in a shorter period. AI has numerous applications in microbiology, including microbial identification and classification, prediction of antimicrobial resistance, microbial genome analysis, disease diagnosis, outbreak surveillance, and drug discovery. Advanced image recognition algorithms assist in the rapid identification of bacterial, viral, and fungal pathogens, while genomic analysis tools facilitate the detection of mutations, virulence factors, and resistance genes. AI also supports the development of precision medicine by enabling personalised treatment strategies based on microbial and patient-specific data. Furthermore, AI-powered epidemiological models help monitor the spread of infectious diseases, predict potential outbreaks, and assist public health authorities in implementing timely preventive measures. Despite its significant advantages, the integration of AI into microbiological research faces several challenges. These include concerns regarding data quality and availability, model interpretability, algorithmic bias, privacy and security of biological data, and ethical and regulatory considerations. Addressing these issues is essential for ensuring the responsible and reliable use of AI technologies in healthcare and research. As computational technologies continue to advance, AI is expected to play an increasingly important role in microbiology by accelerating scientific discoveries, improving diagnostic accuracy, supporting the development of novel antimicrobial agents and vaccines, and strengthening global public health initiatives. This article discusses the diverse applications, advantages, challenges, and future prospects of artificial intelligence in microbiological research.

Keywords: Analysis of the microbiome, Predictive Modelling, Infectious Disease, Big Data Analytics, Computational Biology, Personalised Medicine

How to cite this article:
V. Basil Hans. Artificial Intelligence in Microbiological Research: Methods, Applications and Implications. Research and Reviews: A Journal of Microbiology and Virology. 2026; 16(02):-.
How to cite this URL:
V. Basil Hans. Artificial Intelligence in Microbiological Research: Methods, Applications and Implications. Research and Reviews: A Journal of Microbiology and Virology. 2026; 16(02):-. Available from: https://journals.stmjournals.com/rrjomv/article=2026/view=249058


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Ahead of Print Subscription Review Article
Volume 16
02
Received 09/06/2026
Accepted 28/06/2026
Published 29/06/2026
Publication Time 20 Days
20

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