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Bioprospecting of Extremophilic Microorganisms to Address Environmental Pollution
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Published on: December 30, 2021

Decoding extremophiles: insights from bioinformatics, machine learning, and data-driven approaches.

Maria N Chasapi1,2, Nicholas Kontis2, Robert Lehmann3

  • 1Institute for Fundamental Biomedical Research, BSRC "Alexander Fleming", 34 Fleming Str., Vari, 16672, Greece.

Briefings in Bioinformatics
|May 19, 2026
PubMed
Summary
This summary is machine-generated.

Extremophiles, microorganisms thriving in harsh conditions, are increasingly studied using advanced omics and bioinformatics. AI and machine learning are key to unlocking their biotechnological potential.

Keywords:
bioinformaticscultivationextremophilesmachine learningmetagenomicsmulti-omics

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Biotechnology

Background:

  • Extremophiles inhabit Earth's harshest environments, showcasing remarkable adaptations.
  • Research has shifted from cultivation to data-intensive omics technologies.

Purpose of the Study:

  • To review current extremophile research methodologies and future directions.
  • To highlight the role of bioinformatics, machine learning (ML), and artificial intelligence (AI).

Main Methods:

  • Evolution of cultivation techniques and biomolecule extraction.
  • Application of multi-omics (metagenomics, transcriptomics, proteomics, metabolomics).
  • Utilizing bioinformatics resources and specialized databases for genome annotation.

Main Results:

  • Omics technologies decode the genetic and functional basis of extremophiles.
  • Bioinformatics aids in understanding unique adaptations like protein stabilization.
  • AI and ML predict protein functions and identify novel extremozymes.

Conclusions:

  • Integrating computational biology and AI is crucial for extremophile research.
  • AI/ML can guide the engineering of industrially relevant extremophile strains.
  • This integration promises to unlock the full biotechnological potential of extremophiles.