Progressing microbial genomics: Artificial intelligence and deep learning driven advances in genome analysis and therapeutics DOI Creative Commons

R. Dhaarani,

M. Kiranmai Reddy

Intelligence-Based Medicine, Journal Year: 2025, Volume and Issue: unknown, P. 100251 - 100251

Published: April 1, 2025

Language: Английский

Current Status of Emerging Contaminant Models and Their Applications Concerning the Aquatic Environment: A Review DOI Open Access
Zhuang Liu, Yonghai Gan, Jun Luo

et al.

Water, Journal Year: 2025, Volume and Issue: 17(1), P. 85 - 85

Published: Jan. 1, 2025

Increasing numbers of emerging contaminants (ECs) detected in water environments require a detailed understanding these chemicals’ fate, distribution, transport, and risk aquatic ecosystems. Modeling is useful approach for determining ECs’ characteristics their behaviors environments. This article proposes systematic taxonomy EC models addresses gaps the comprehensive analysis applications. The reviewed include conventional quality models, multimedia fugacity machine learning (ML) models. Conventional have higher prediction accuracy spatial resolution; nevertheless, they are limited functionality can only be used to predict contaminant concentrations Fugacity excellent at depicting how travel between different environmental media, but cannot directly analyze variations parts same media because model assumes that constant within compartment. Compared other ML applied more scenarios, such as identification assessments, rather than being confined concentrations. In recent years, with rapid development artificial intelligence, surpassed becoming one newest hotspots study ECs. primary challenge faced by outcomes difficult interpret understand, this influences practical value an some extent.

Language: Английский

Citations

2
Advanced omics approach and sustainable strategies for heavy metal microbial remediation in contaminated environments DOI
Vaishali Kumar, Vandana Singh, Soumya Pandit

et al.

Bioresource Technology Reports, Journal Year: 2025, Volume and Issue: unknown, P. 102040 - 102040

Published: Jan. 1, 2025

Language: Английский

Citations

2
Microbial augmented aerobic composting for effective phthalates degradation in activated sludge DOI
Bogui Pan,

Hong Tian,

Qifeng Liang

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 377, P. 124630 - 124630

Published: Feb. 21, 2025

Language: Английский

Citations

0
Progressing microbial genomics: Artificial intelligence and deep learning driven advances in genome analysis and therapeutics DOI Creative Commons

R. Dhaarani,

M. Kiranmai Reddy

Intelligence-Based Medicine, Journal Year: 2025, Volume and Issue: unknown, P. 100251 - 100251

Published: April 1, 2025

Language: Английский

Citations

0