Artificial Intelligence Driven Bioinformatics for Sustainable Bioremediation: Integrating Computational Intelligence with Ecological Restoration

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This is a Quantitative Study study.

Kashif R. Siddique; Debajyoti Bose; Riya Bhattacharya; Raul V. Rodriguez; Aritra Ray

doi:10.1039/d5va00240k

January 1, 2025Environmental Science AdvancesOpen Access

Artificial Intelligence Driven Bioinformatics for Sustainable Bioremediation: Integrating Computational Intelligence with Ecological Restoration

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Key Points

The integration of AI with bioinformatics improves bioremediation outcomes in polluted environments, offering innovative solutions.
Studies show that utilizing microorganisms can effectively break down heavy metals and organic contaminants in ecosystems.
The AI-driven approach allows for rapid data analysis and modeling, significantly enhancing remediation techniques for environmental pollutants.
These findings emphasize the importance of combining technology with ecological strategies to foster sustainable environmental practices.

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Implication

This analysis integrates artificial intelligence and bioinformatics to enhance bioremediation strategies, highlighting the need for ecological restoration.

Abstract

Environmental pollution from heavy metals and untreated wastewater poses significant risks to ecosystems and human health, highlighting the urgent need for innovative remediation strategies. Bioremediation employs microorganisms to break down...

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Siddique et al. (2025) studied this question.

synapsesocial.com/papers/68de5da283cbc991d0a20794 https://doi.org/10.1039/d5va00240k

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Artificial Intelligence Driven Bioinformatics for Sustainable Bioremediation: Integrating Computational Intelligence with Ecological Restoration

Key Points

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Implication

Abstract

Discussion

Cite This Study

Artificial Intelligence Driven Bioinformatics for Sustainable Bioremediation: Integrating Computational Intelligence with Ecological Restoration

Key Points

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Implication

Abstract

Discussion

Cite This Study

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