Microbial Informatics in Association with Disease Biology: A Multi-Omics Approach on Computational Microbiology Applications
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Abstract
Background: Bioinformatics is a scientific sub-discipline that covers the area of biology at multi-disciplinary levels of microbiology, immunology, molecular biology, biochemistry, genetics, proteomics etc. This is a technical analysis of computational biology that collect and convert raw data into storage to analyse and disseminate this biological information such as, De-oxy-ribonucleic Acid, protein, amino acid sequences, alpha-fold 3-Dimensional structure, taxonomic hierarchy, polypeptides, messenger Ribonucleic Acid, chemical origin into annotated databases. Aim: Bioinformatics tools and programs are used to interpret and develop biological raw data and efficiently manage through accession database to create statistical approaches for evaluating relationships between large datasets. Scope: The advancement of genome sequencing technologies and metagenomic analysis have well developed microbial informatics applications to study microorganisms and their functionality based on microbial interactions in natural and artificial environments. This large amount of microbial information has been structured, indexed and correlated with existing experimental evidences. The bioinformatics solutions of overwhelming research parameters are cross-connected with information science and microbiology in relevance. In the recent scenario, artificial intelligence techniques, aggregated statistical analysis methods and large-scale data input system have provided microbiology to evolve with data science. Key Insights: ‘‘Clinical Microbiology Informatics’’ deals with detection, identification and confirmation of antimicrobial susceptibility testing and communicates with clinicians about the importance of clinically relevant microbes. Clinical microorganisms in pathogenic diseases provide insights into genetic and molecular mechanisms of pathogen through bioinformatics analysis. Microbial bioinformatics applications are used for pathogen identification, characterization, mutation, detection of virulence factors, microbial engineering, vaccine targets, drug and vaccine combinations, disease regulation, host-immune evasion and diagnostic approaches. Future Perspective: This study highlights the critical significance of computational microbiology in comprehending microbial pathogens and their interactions with hosts by examining the nexus between microbial informatics and disease biology. Researchers can examine microbial populations, analyze genomic data, and pinpoint virulence factors linked to a range of illnesses by utilizing cutting-edge bioinformatics methods. We go on recent applications that improve our comprehension of microbial dynamics in illness contexts, including metagenomics, machine learning, and network analysis. The analysis highlights the potential of microbial informatics to guide treatment plans, enhance diagnostic techniques, and support vaccine research, all of which will ultimately lead to improvements in public health.
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Copyright (c) 2025 Debaleena Samanta, MSc, Malavika Bhattacharya, PhD
This work is licensed under a Creative Commons Attribution 4.0 International License.
Creative Commons License All articles published in Annals of Medicine and Medical Sciences are licensed under a Creative Commons Attribution 4.0 International License.
Debaleena Samanta, MSc, Department of Biotechnology, Techno India University, West Bengal, India.
Department of Biotechnology, Techno India University, West Bengal, India.
Malavika Bhattacharya, PhD, Department of Biotechnology, Techno India University, West Bengal, India.
Department of Biotechnology, Techno India University, West Bengal, India.
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