{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T18:59:40Z","timestamp":1792695580625,"version":"4.5.0"},"reference-count":154,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>Hydrocarbon contamination, particularly with polycyclic aromatic hydrocarbons (PAHs), poses a significant environmental challenge due to its persistence and carcinogenic effects on ecosystems and human health globally. This review explores how ML algorithms can enhance the efficiency of bio-augmentation and phytoremediation through predictive modeling, real-time optimization of microbial consortia, and plant species selection. Traditional bioremediation methods, such as bioaugmentation and phytoremediation, are characterized by slow degradation rates and sub-optimal performance in complex, multi-contaminant environmental milieus. The use of machine learning (ML) models with multi-omics data presents an advanced predictive approach to optimizing bioremediation processes by providing a systematic understanding of microbial and plant-mediated hydrocarbon degradation strategies and processes. ML models can predict which microbial strains or plant species will effectively degrade hydrocarbons under specific environmental conditions by utilizing supervised learning methods such as support vector machines and neural networks. Additionally, the combination of multi-omics data with ML facilitates the identification of critical genes, enzymes, and metabolic pathways involved in the degradation of hydrocarbons, and offers insights into the molecular mechanisms which drive the bioremediation process. The translation of laboratory-based ML models into large-scale, real-world bioremediation strategy is hindered by the complex, dynamic nature of our contaminated environments. This review paper showcases these hinderances and provides a direction for future research, including the development of field-deployable technologies, adaptive ML models, and real-time environmental monitoring strategies. The integration of ML with multi-omics holds substantial promise for enhanced efficiency, adaptability, and scalability of bioremediation strategies which ultimately mitigates carcinogenic risks often associated with hydrocarbon-polluted lithosphere.<\/jats:p>","DOI":"10.3389\/fmicb.2026.1742848","type":"journal-article","created":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T06:57:49Z","timestamp":1772693869000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Machine learning approaches for data-driven hydrocarbon bioaugmentation and phytoremediation: the role of multi-omics insights"],"prefix":"10.3389","volume":"17","author":[{"given":"Ugochukwu Chukwuma","family":"Okafor","sequence":"first","affiliation":[{"name":"Department of Applied Microbiology and Brewing, Faculty of Biosciences, Nnamdi Azikiwe University","place":["Awka, Nigeria"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saeed M.","family":"Alghamdi","sequence":"additional","affiliation":[{"name":"Respiratory Care Program, Clinical Technology Department, Faculty of Applied Medical Sciences, Umm Al-Qura University","place":["Makkah, Saudi Arabia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorna","family":"Anguilano","sequence":"additional","affiliation":[{"name":"Experimental Techniques Centre, Brunel University London","place":["Uxbridge, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, Brunel University London","place":["Uxbridge, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,3,5]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"11786302251343767","DOI":"10.1177\/11786302251343767","article-title":"Public health effects of polycyclic aromatic hydrocarbons exposure through air, water, soil, and food in Ghana: possible economic burden","volume":"19","author":"Abdulai","year":"2025","journal-title":"Environmental Health Insights"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"100885\u2013100885","DOI":"10.1016\/j.atech.2025.100885","article-title":"Optimization of irrigation and fertigation in smart agriculture: an IoT-based micro-services framework","volume":"11","author":"Adamo","year":"2025","journal-title":"Smart Agricultural Technology"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"18477","DOI":"10.1073\/pnas.2000585117","article-title":"Machine learning classification can reduce false positives in structure-based virtual screening","volume":"117","author":"Adeshina","year":"2020","journal-title":"Proc. Natl. Acad. Sci."},{"key":"ref4","doi-asserted-by":"publisher","first-page":"001-009","DOI":"10.26502\/jesph.96120043","article-title":"Introduction of petroleum hydrocarbons contaminants and its human effects","volume":"3","author":"Adipah","year":"2018","journal-title":"J. Environ. Sci. Public Health"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"334","DOI":"10.2174\/1389202921999200623133240","article-title":"Unravelling the role of Rhizospheric plant-microbe synergy in phytoremediation: A genomic perspective","volume":"21","author":"Agarwal","year":"2020","journal-title":"Curr. Genomics"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"21","DOI":"10.12688\/openresafrica.13383.1","article-title":"Cost reduction strategies in the remediation of petroleum hydrocarbon contaminated soil","volume":"5","author":"Ahmed","year":"2022","journal-title":"Open Research Africa"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"788","DOI":"10.30574\/wjarr.2024.24.1.3099","article-title":"AI-driven monitoring systems for bioremediation: real-time data analysis and predictive modelling","volume":"24","author":"Akintola","year":"2024","journal-title":"World J. Adv. Res. Rev."},{"key":"ref8","doi-asserted-by":"publisher","first-page":"3036","DOI":"10.3390\/pr11103036","article-title":"Advancing eco-sustainable bioremediation for hydrocarbon contaminants: challenges and solutions","volume":"11","author":"Alaidaroos","year":"2023","journal-title":"PRO"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18332\/tid\/205871","article-title":"Usage patterns, knowledge, and attitudes of healthcare providers regarding e-cigarettes: a cross-sectional study in Saudi Arabia","volume":"23","author":"Alasmari","year":"2025","journal-title":"Tob. Induc. Dis."},{"key":"ref10","doi-asserted-by":"publisher","first-page":"1517","DOI":"10.3390\/healthcare9111517","article-title":"Digital health platforms in Saudi Arabia: determinants from the COVID-19 pandemic experience","volume":"9","author":"Alghamdi","year":"2021","journal-title":"Healthcare"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"2550823","DOI":"10.1080\/11287462.2025.2550823","article-title":"Navigating ethical challenges in digital transformation: insights on climate adaptation, microbiology, healthcare, robotics, and AI under the EU AI act: an experts panel discussion","volume":"36","author":"Alghamdi","year":"2025","journal-title":"Glob. Bioeth."},{"key":"ref12","first-page":"477","volume-title":"Artificial Intelligence and Machine Learning in Health Care and Medical Sciences. Health Informatics","author":"Aliferis","year":"2024"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1016\/j.hrtlng.2025.07.005","article-title":"Smoking prevalence among stroke patients in Saudi Arabia: A systematic review and meta-analysis","volume":"74","author":"Alqahtani","year":"2025","journal-title":"Heart Lung"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"5753","DOI":"10.3390\/jcm14165753","article-title":"Asthma control among adults in Saudi Arabia: a systematic review and meta-analysis","volume":"14","author":"Alqahtani","year":"2025","journal-title":"PubMed"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"133572","DOI":"10.1016\/j.chemosphere.2022.133572","article-title":"Remediation of soil polluted with petroleum hydrocarbons and its reuse for agriculture: recent progress, challenges, and perspectives","volume":"293","author":"Ambaye","year":"2022","journal-title":"Chemosphere"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"824451","DOI":"10.3389\/fgene.2022.824451","article-title":"Machine learning: a new prospect in multi-omics data analysis of cancer","volume":"13","author":"Arjmand","year":"2022","journal-title":"Front. Genet."},{"key":"ref17","doi-asserted-by":"publisher","first-page":"e38683","DOI":"10.1016\/j.heliyon.2024.e38683","article-title":"Phytoremediation strategies for mitigating environmental toxicants","volume":"10","author":"Aryal","year":"2024","journal-title":"Heliyon"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1038\/s41579-023-00984-1","article-title":"Machine learning for microbiologists","volume":"22","author":"Asnicar","year":"2023","journal-title":"Nat. Rev. Microbiol."},{"key":"ref19","doi-asserted-by":"publisher","first-page":"101220\u2013101220","DOI":"10.1016\/j.envc.2025.101220","article-title":"Harnessing microbes and plants for bioremediation of heavy metal contaminants: current paradigms and future perspectives","volume":"20","author":"Ayub","year":"2025","journal-title":"Environ. Challenges"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"484","DOI":"10.3390\/toxics10080484","article-title":"Recent strategies for bioremediation of emerging pollutants: A review for a green and sustainable environment","volume":"10","author":"Bala","year":"2022","journal-title":"Toxics"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1080\/10937404.2022.2164390","article-title":"Polycyclic aromatic hydrocarbons (PAHs): updated aspects of their determination, kinetics in the human body, and toxicity","volume":"26","author":"Barbosa","year":"2023","journal-title":"J. Toxic. Environ. Health, Part B"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1016\/j.envpol.2016.07.065","article-title":"Oil spills and their impacts on sand beach invertebrate communities: A literature review","volume":"218","author":"Bejarano","year":"2016","journal-title":"Environ. Pollut."},{"key":"ref23","doi-asserted-by":"crossref","DOI":"10.1007\/978-981-13-3426-9","volume-title":"Bioremediation of industrial waste for environmental safety","author":"Bharagava","year":"2020"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"e578","DOI":"10.7717\/peerj-cs.578","article-title":"IoT-IIRS: internet of things based intelligent-irrigation recommendation system using machine learning approach for efficient water usage","volume":"7","author":"Bhoi","year":"2021","journal-title":"PeerJ Computer Science"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"1504254","DOI":"10.3389\/fmicb.2025.1504254","article-title":"AI-driven optimization of bioremediation strategies for river pollution: a comprehensive review and future directions","volume":"16","author":"Blessing","year":"2025","journal-title":"Front. Microbiol."},{"key":"ref26","doi-asserted-by":"publisher","first-page":"6348","DOI":"10.3390\/ijms23116348","article-title":"Benzo[a]pyrene-environmental occurrence, human exposure, and mechanisms of toxicity","volume":"23","author":"Bukowska","year":"2022","journal-title":"Int. J. Mol. Sci."},{"key":"ref27","doi-asserted-by":"publisher","first-page":"e0215121","DOI":"10.1128\/aem.02151-21","article-title":"Metagenomic and Metatranscriptomic responses of chemical dispersant application during a marine Dilbit spill","volume":"88","author":"Cao","year":"2022","journal-title":"Appl. Environ. Microbiol."},{"key":"ref28","doi-asserted-by":"publisher","first-page":"867","DOI":"10.3390\/ijerph21070867","article-title":"Random Forest and feature importance measures for discriminating the Most influential environmental factors in predicting cardiovascular and respiratory diseases","volume":"21","author":"Cappelli","year":"2024","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"ref29","volume-title":"Encyclop\u00e6dia Britannica","author":"Carey","year":"2018"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"119569","DOI":"10.1016\/j.envpol.2022.119569","article-title":"Natural additives contribute to hydrocarbon and heavy metal co-contaminated soil remediation","volume":"307","author":"Cavazzoli","year":"2022","journal-title":"Environ. Pollut."},{"key":"ref31","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1007\/s44274-025-00217-7","article-title":"Role of fungi, bacteria and microalgae in bioremediation of emerging pollutants with special reference to pesticides, heavy metals and pharmaceuticals","volume":"3","author":"Chakraborty","year":"2025","journal-title":"Discover Environment"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"5758","DOI":"10.3390\/app13095758","article-title":"Assessing the performance of machine learning algorithms for soil classification using cone penetration test data","volume":"13","author":"Chala","year":"2023","journal-title":"Appl. Sci."},{"key":"ref33","doi-asserted-by":"publisher","first-page":"e315","DOI":"10.1002\/mco2.315","article-title":"Applications of multi-omics analysis in human diseases","volume":"4","author":"Chen","year":"2023","journal-title":"MedComm"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"111164","DOI":"10.1016\/j.ecolmodel.2025.111164","article-title":"Algorithms going wild \u2013 a review of machine learning techniques for terrestrial ecology","volume":"506","author":"Cipriano","year":"2025","journal-title":"Ecol. Model."},{"key":"ref35","doi-asserted-by":"publisher","first-page":"848","DOI":"10.3390\/microorganisms13040848","article-title":"Assessing microbial activity and Rhizoremediation in hydrocarbon and heavy metal-impacted soil","volume":"13","author":"Conlon","year":"2025","journal-title":"Microorganisms"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"1709","DOI":"10.3390\/microbiolres15030113","article-title":"Multifaceted applications of synthetic microbial communities: advances in biomedicine, bioremediation, and industry","volume":"15","author":"Contreras-Salgado","year":"2024","journal-title":"Microbiol. Res."},{"key":"ref37","doi-asserted-by":"publisher","first-page":"229","DOI":"10.3390\/environments12070229","article-title":"A review of persistent soil contaminants: assessment and remediation strategies","volume":"12","author":"Correia","year":"2025","journal-title":"Environments"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4061\/2011\/941810","article-title":"Microbial degradation of petroleum hydrocarbon contaminants: an overview","volume":"2011","author":"Das","year":"2011","journal-title":"Biotechnol. Res. Int."},{"key":"ref39","doi-asserted-by":"publisher","first-page":"842","DOI":"10.1039\/d4va00203b","article-title":"Environmental restoration of polyaromatic hydrocarbon-contaminated soil through sustainable rhizoremediation: insights into bioeconomy and high-throughput systematic analysis","volume":"4","author":"Das","year":"2025","journal-title":"Environ. Sci. Adv."},{"key":"ref40","doi-asserted-by":"publisher","first-page":"6714","DOI":"10.1128\/aem.70.11.6714-6725.2004","article-title":"Identification and functional analysis of two aromatic-ring-hydroxylating dioxygenases from a Sphingomonas strain that degrades various polycyclic aromatic hydrocarbons","volume":"70","author":"Deman\u00e8che","year":"2004","journal-title":"Appl. Environ. Microbiol."},{"key":"ref41","doi-asserted-by":"publisher","first-page":"1333076","DOI":"10.3389\/fmicb.2024.1333076","article-title":"Rhizosphere microbial community enrichment processes in healthy and diseased plants: implications of soil properties on biomarkers","volume":"15","author":"Deng","year":"2024","journal-title":"Front. Microbiol."},{"key":"ref42","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1002\/etc.4906","article-title":"Ingestion and dermal cancer risk via exposure to polycyclic aromatic hydrocarbon\u2013contaminated soils in an oil-producing community, Niger Delta, Nigeria","volume":"40","author":"Enuneku","year":"2020","journal-title":"Environ. Toxicol. Chem."},{"key":"ref43","doi-asserted-by":"publisher","first-page":"4009105","DOI":"10.1155\/tswj\/4009105","article-title":"Isolation and identification of black oil-degrading bacteria from lubricant-contaminated soil in northern Baghdad, Iraq","volume":"2025","author":"Faisal","year":"2025","journal-title":"Sci. World J."},{"key":"ref44","doi-asserted-by":"publisher","first-page":"100553","DOI":"10.1016\/j.bdr.2025.100553","article-title":"Deep neural network modeling for financial time series analysis","volume":"41","author":"Fang","year":"2025","journal-title":"Big Data Res."},{"key":"ref45","doi-asserted-by":"publisher","first-page":"e25924","DOI":"10.1016\/j.heliyon.2024.e25924","article-title":"Contamination of groundwater by petroleum hydrocarbons: impact of fuel stations in residential areas","volume":"10","author":"Fei-Baffoe","year":"2024","journal-title":"Heliyon"},{"key":"ref46","doi-asserted-by":"publisher","first-page":"11779322251371117","DOI":"10.1177\/11779322251371117","article-title":"Metagenomic insights into biopile remediation of petroleum-contaminated soil using chicken droppings in Rivers state, Nigeria","volume":"19","author":"Fenibo","year":"2025","journal-title":"Bioinform. Biol. Insights"},{"key":"ref47","doi-asserted-by":"publisher","first-page":"1098308","DOI":"10.3389\/frai.2023.1098308","article-title":"Missing data in multi-omics integration: recent advances through artificial intelligence","volume":"6","author":"Flores","year":"2023","journal-title":"Front. Artif. Intell."},{"key":"ref48","doi-asserted-by":"publisher","first-page":"854","DOI":"10.3390\/microorganisms13040854","article-title":"Assessment of soil health through metagenomic analysis of bacterial diversity in Russian black soil","volume":"13","author":"Galanova","year":"2025","journal-title":"Microorganisms"},{"key":"ref49","doi-asserted-by":"publisher","first-page":"848","DOI":"10.3390\/biology13110848","article-title":"Integrating molecular perspectives: strategies for comprehensive multi-omics integrative data analysis and machine learning applications in transcriptomics, proteomics, and metabolomics","volume":"13","author":"Godoy","year":"2024","journal-title":"Biology"},{"key":"ref50","doi-asserted-by":"publisher","first-page":"108930","DOI":"10.1016\/j.envint.2024.108930","article-title":"Integrating multi-omics with environmental data for precision health: A novel analytic framework and case study on prenatal mercury induced childhood fatty liver disease","volume":"190","author":"Goodrich","year":"2024","journal-title":"Environ. Int."},{"key":"ref51","doi-asserted-by":"publisher","first-page":"5777","DOI":"10.3390\/cimb46060345","article-title":"Multi omics applications in biological systems","volume":"46","author":"Gutierrez Reyes","year":"2024","journal-title":"Curr. Issues Mol. Biol."},{"key":"ref52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jhazmat.2009.03.137","article-title":"Biodegradation aspects of polycyclic aromatic hydrocarbons (PAHs): a review","volume":"169","author":"Haritash","year":"2009","journal-title":"J. Hazard. Mater."},{"key":"ref53","doi-asserted-by":"publisher","first-page":"1551","DOI":"10.3390\/genes15121551","article-title":"From omics to multi-omics: A review of advantages and tradeoffs","volume":"15","author":"Hayes","year":"2024","journal-title":"Genes"},{"key":"ref54","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1038\/s43705-022-00182-9","article-title":"Machine learning and deep learning applications in microbiome research","volume":"2","author":"Hern\u00e1ndez Medina","year":"2022","journal-title":"ISME Commun."},{"key":"ref55","doi-asserted-by":"publisher","first-page":"561506","DOI":"10.3389\/fmicb.2020.561506","article-title":"Metagenomic insights into the mechanisms for biodegradation of polycyclic aromatic hydrocarbons in the oil supply chain","volume":"11","author":"Hidalgo","year":"2020","journal-title":"Front. Microbiol."},{"key":"ref56","doi-asserted-by":"publisher","first-page":"142860","DOI":"10.1016\/j.chemosphere.2024.142860","article-title":"Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: A comprehensive review and future perspective","volume":"362","author":"Ibrahim","year":"2024","journal-title":"Chemosphere"},{"key":"ref57","doi-asserted-by":"publisher","first-page":"100283","DOI":"10.1016\/j.stress.2023.100283","article-title":"Advancing environmental sustainability through microbial reprogramming in growth improvement, stress alleviation, and phytoremediation","volume":"10","author":"Iqbal","year":"2023","journal-title":"Plant Stress"},{"key":"ref58","doi-asserted-by":"publisher","first-page":"51","DOI":"10.12691\/jephh-6-2-2","article-title":"Petroleum hydrocarbons contamination of surface water and groundwater in the Niger Delta region of Nigeria","volume":"6","author":"Ite","year":"2018","journal-title":"J. Environ. Pollut. Hum. Health"},{"key":"ref59","author":"Jameson","year":"2019"},{"key":"ref60","doi-asserted-by":"publisher","first-page":"140476","DOI":"10.1016\/j.chemosphere.2023.140476","article-title":"Integrating artificial intelligence, machine learning, and deep learning approaches into remediation of contaminated sites: a review","volume":"345","author":"Janga","year":"2023","journal-title":"Chemosphere"},{"key":"ref61","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13042-023-02083-2","article-title":"Fairness issues, current approaches, and challenges in machine learning models","volume":"15","author":"Jui","year":"2024","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref62","doi-asserted-by":"publisher","first-page":"16568","DOI":"10.3390\/su142416568","article-title":"Evaluating different soil amendments as bioremediation strategy for wetland soil contaminated by crude oil","volume":"14","author":"Jumbo","year":"2022","journal-title":"Sustainability"},{"key":"ref63","doi-asserted-by":"publisher","first-page":"100203","DOI":"10.1016\/j.envadv.2022.100203","article-title":"Phytoremediation: mechanisms, plant selection and enhancement by natural and synthetic agents","volume":"8","author":"Kafle","year":"2022","journal-title":"Environmental Advances"},{"key":"ref64","doi-asserted-by":"publisher","first-page":"2244","DOI":"10.22207\/jpam.18.4.28","article-title":"Microbial bioremediation of petroleum contaminated soil: structural complexity, degradation dynamics and advanced remediation techniques","volume":"18","author":"Kakde","year":"2024","journal-title":"J. Pure Appl. Microbiol."},{"key":"ref65","doi-asserted-by":"publisher","first-page":"29","DOI":"10.47941\/ijce.2139","article-title":"Internet of things (IoT) for environmental monitoring","volume":"6","author":"Katie","year":"2024","journal-title":"Int. J. Comput. Eng."},{"key":"ref66","doi-asserted-by":"publisher","first-page":"104572","DOI":"10.1016\/j.eti.2025.104572","article-title":"Current situation and future outlook petroleum hydrocarbons in marine systems: a review","volume":"40","author":"Kianfar","year":"2025","journal-title":"Environ. Technol. Innov."},{"key":"ref67","doi-asserted-by":"publisher","first-page":"144531","DOI":"10.1016\/j.scitotenv.2020.144531","article-title":"Rice genotype\u2019s responses to arsenic stress and cancer risk: the effects of integrated birnessite-modified rice hull biochar-water management applications","volume":"768","author":"Kumarathilaka","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref68","doi-asserted-by":"publisher","first-page":"e08995","DOI":"10.1016\/j.heliyon.2022.e08995","article-title":"Practical limitations of bioaugmentation in treating heavy metal contaminated soil and role of plant growth promoting bacteria in phytoremediation as a promising alternative approach","volume":"8","author":"Kurniawan","year":"2022","journal-title":"Heliyon"},{"key":"ref69","doi-asserted-by":"publisher","first-page":"109365","DOI":"10.1016\/j.envint.2025.109365","article-title":"Advances in environmental pollutant detection techniques: enhancing public health monitoring and risk assessment","volume":"197","author":"Li","year":"2025","journal-title":"Environ. Int."},{"key":"ref70","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1186\/s40538-025-00797-9","article-title":"Phytoremediation of organic pollution using leguminous plants and auxiliary additives: principles and advantages","volume":"12","author":"Liu","year":"2025","journal-title":"Chem. Biol. Technol. Agric."},{"key":"ref71","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.still.2015.07.006","article-title":"A comprehensive support vector machine-based classification model for soil quality assessment","volume":"155","author":"Liu","year":"2016","journal-title":"Soil Tillage Res."},{"key":"ref72","doi-asserted-by":"publisher","first-page":"916\u2013916","DOI":"10.3390\/p13030916","article-title":"Microbial degradation of soil organic pollutants: mechanisms, challenges, and advances in forest ecosystem management","volume":"13","author":"Liu","year":"2025","journal-title":"PRO"},{"key":"ref73","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1186\/1471-2105-5-172","article-title":"Incremental genetic K-means algorithm and its application in gene expression data analysis","volume":"5","author":"Lu","year":"2004","journal-title":"BMC Bioinformatics"},{"key":"ref74","doi-asserted-by":"publisher","first-page":"9963","DOI":"10.3390\/su16229963","article-title":"Generative AI for consumer behavior prediction: techniques and applications","volume":"16","author":"Madanchian","year":"2024","journal-title":"Sustainability"},{"key":"ref75","doi-asserted-by":"publisher","first-page":"100026","DOI":"10.1016\/j.temicr.2025.100026","article-title":"Emerging microbial remediation methods for rejuvenation of pesticide-contaminated sites","volume":"1","author":"Mahalle","year":"2025","journal-title":"Total Environ. Microbiol."},{"key":"ref76","doi-asserted-by":"publisher","first-page":"133948","DOI":"10.1016\/j.chemosphere.2022.133948","article-title":"Polycyclic aromatic hydrocarbon and its effects on human health: an overeview","volume":"296","author":"Mallah","year":"2022","journal-title":"Chemosphere"},{"key":"ref77","doi-asserted-by":"publisher","first-page":"11069","DOI":"10.3390\/app122111069","article-title":"A mathematical model for bioremediation of hydrocarbon-contaminated soils","volume":"12","author":"Martins","year":"2022","journal-title":"Appl. Sci."},{"key":"ref78","doi-asserted-by":"publisher","first-page":"37","DOI":"10.15586\/computationalbiology.2019.ch3","article-title":"Deep learning in omics data analysis and precision medicine","author":"Martorell-Marug\u00e1n","year":"2019","journal-title":"Comput. Biol."},{"key":"ref79","doi-asserted-by":"publisher","first-page":"626436","DOI":"10.3389\/fmicb.2021.626436","article-title":"Bioaugmentation of native Fungi, an efficient strategy for the bioremediation of an aged industrially polluted soil with heavy hydrocarbons","volume":"12","author":"Medaura","year":"2021","journal-title":"Front. Microbiol."},{"key":"ref80","doi-asserted-by":"publisher","first-page":"2039","DOI":"10.3390\/ijms17122039","article-title":"Internet databases of the properties, enzymatic reactions, and metabolism of small molecules\u2014search options and applications in food science","volume":"17","author":"Minkiewicz","year":"2016","journal-title":"Int. J. Mol. Sci."},{"key":"ref81","doi-asserted-by":"publisher","first-page":"1653","DOI":"10.3390\/plants12081653","article-title":"Phytoremediation as an effective remedy for removing trace elements from ecosystems","volume":"12","author":"Mocek-P\u0142\u00f3ciniak","year":"2023","journal-title":"Plants"},{"key":"ref82","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/s00122-025-04948-2","article-title":"Integrating multi-omics and machine learning for disease resistance prediction in legumes","volume":"138","author":"Mohamedikbal","year":"2025","journal-title":"Theor. Appl. Genet."},{"key":"ref83","doi-asserted-by":"publisher","first-page":"1108","DOI":"10.1038\/s41598-017-01126-3","article-title":"Bioinformatic approaches including predictive metagenomic profiling reveal characteristics of bacterial response to petroleum hydrocarbon contamination in diverse environments","volume":"7","author":"Mukherjee","year":"2017","journal-title":"Sci. Rep."},{"key":"ref84","doi-asserted-by":"publisher","first-page":"710","DOI":"10.3390\/microorganisms11030710","article-title":"Current trends in bioaugmentation tools for bioremediation: a critical review of advances and knowledge gaps","volume":"11","author":"Muter","year":"2023","journal-title":"Microorganisms"},{"key":"ref85","doi-asserted-by":"publisher","first-page":"100142","DOI":"10.1016\/j.clcb.2025.100142","article-title":"Exploring the role of nature-based solutions and emerging technologies in advancing circular and sustainable agriculture: an opinionated review for environmental resilience","volume":"10","author":"Nassary","year":"2025","journal-title":"Clean. Circ. Bioecon."},{"key":"ref86","doi-asserted-by":"publisher","first-page":"27961","DOI":"10.1038\/s41598-025-13545-8","article-title":"Whole genome sequence of petroleum hydrocarbon degrading novel strain Microbacter sp. EMBS2025 isolated from Chilika Lake, Odisha, India","volume":"15","author":"Nayarisseri","year":"2025","journal-title":"Sci. Rep."},{"key":"ref87","doi-asserted-by":"publisher","first-page":"436","DOI":"10.3390\/agriculture10100436","article-title":"Machine learning for plant breeding and biotechnology","volume":"10","author":"Niazian","year":"2020","journal-title":"Agriculture"},{"key":"ref88","doi-asserted-by":"publisher","first-page":"114313","DOI":"10.1016\/j.jenvman.2021.114313","article-title":"Bioaugmentation as a green technology for hydrocarbon pollution remediation. Problems and prospects","volume":"304","author":"Nwankwegu","year":"2022","journal-title":"J. Environ. Manag."},{"key":"ref89","doi-asserted-by":"publisher","first-page":"846","DOI":"10.3390\/ijerph13090846","article-title":"Bioaugmentation: an emerging strategy of industrial wastewater treatment for reuse and discharge","volume":"13","author":"Nzila","year":"2016","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"ref90","doi-asserted-by":"publisher","first-page":"24","DOI":"10.53623\/tasp.v3i1.132","article-title":"Evaluation of the impact of crude oil contamination on soil\u2019s physicochemical characteristics, micro-flora and crop yield","volume":"3","author":"Okafor","year":"2023","journal-title":"Trop. Aquat. Soil Pollut."},{"key":"ref91","doi-asserted-by":"publisher","first-page":"75","DOI":"10.12691\/jaem-4-4-2","article-title":"Bioremediation of crude oil-polluted soil using broiler-chicken droppings","volume":"4","author":"Okafor","year":"","journal-title":"Journal of Applied & Environmental Microbiology"},{"key":"ref92","first-page":"62","article-title":"Effect of chicken droppings amendment on bioremediation of crude oil polluted soil","volume":"6","author":"Okafor","year":"","journal-title":"Eur. J. Exp. Biol."},{"key":"ref93","doi-asserted-by":"publisher","first-page":"311","DOI":"10.5897\/AJEST2017.2350","article-title":"An appraisal of phytoremediation as an alternative and effective remediation technology for crude oil- contaminated soils: a review","volume":"16","author":"Oyedeji","year":"2022","journal-title":"Afr. J. Environ. Sci. Technol."},{"key":"ref94","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/s42452-024-06381-4","article-title":"Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health\u2014a review","volume":"7","author":"Pace","year":"2025","journal-title":"Deleted J."},{"key":"ref95","doi-asserted-by":"publisher","first-page":"2484","DOI":"10.3390\/microorganisms12122484","article-title":"Advances in the degradation of polycyclic aromatic hydrocarbons by yeasts: A review","volume":"12","author":"Padilla-Garfias","year":"2024","journal-title":"Microorganisms"},{"key":"ref96","first-page":"1","volume-title":"Microbial Action on Hydrocarbons","author":"Paniagua-Michel","year":"2018"},{"key":"ref97","doi-asserted-by":"publisher","first-page":"562813","DOI":"10.3389\/fmicb.2020.562813","article-title":"Polycyclic aromatic hydrocarbons: sources, toxicity, and remediation approaches","volume":"11","author":"Patel","year":"2020","journal-title":"Front. Microbiol."},{"key":"ref98","doi-asserted-by":"publisher","first-page":"19640","DOI":"10.1007\/s11356-017-9496-1","article-title":"Hydrocarbon degradation potential and plant growth-promoting activity of culturable endophytic bacteria of Lotus corniculatus and Oenothera biennis from a long-term polluted site","volume":"24","author":"Pawlik","year":"2017","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref99","doi-asserted-by":"publisher","first-page":"30453","DOI":"10.1038\/s41598-025-15517-4","article-title":"Comparative analysis of machine learning models for detecting water quality anomalies in treatment plants","volume":"15","author":"Prabu","year":"2025","journal-title":"Sci. Rep."},{"key":"ref100","doi-asserted-by":"publisher","first-page":"827","DOI":"10.3389\/fmicb.2019.00827","article-title":"Application of machine learning in microbiology","volume":"10","author":"Qu","year":"2019","journal-title":"Front. Microbiol."},{"key":"ref101","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1007\/s12032-022-01711-1","article-title":"Artificial intelligence and machine learning in precision and genomic medicine","volume":"39","author":"Quazi","year":"2022","journal-title":"Med. Oncol."},{"key":"ref102","author":"Ram","year":"2026"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.21203\/rs.3.rs-5690795\/v1","article-title":"Effective phytoremediation of soil contamination through native Iranian hyperaccumulator plant species","author":"Rasti","year":"2024","journal-title":"Res. Square"},{"key":"ref104","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1007\/s00299-024-03153-7","article-title":"Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity","volume":"43","author":"Raza","year":"2024","journal-title":"Plant Cell Rep."},{"key":"ref105","doi-asserted-by":"publisher","first-page":"107739","DOI":"10.1016\/j.biotechadv.2021.107739","article-title":"Using machine learning approaches for multi-omics data analysis: a review","volume":"49","author":"Reel","year":"2021","journal-title":"Biotechnol. Adv."},{"key":"ref106","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1007\/s40201-023-00865-y","article-title":"Bioaugmentation and phytoremediation wastewater treatment process as a viable alternative for pesticides removal: case of pentachlorophenol Werheni Ammeri, Soulwene Kouki, Hassen, W., Maroua Oueslati, Najla Sadfi-Zouaoui, &","volume":"21","author":"Rim Hassen","year":"2023","journal-title":"J. Environ. Health Sci. Eng."},{"key":"ref107","doi-asserted-by":"publisher","first-page":"101185","DOI":"10.1016\/j.patter.2025.101185","article-title":"Unraveling overoptimism and publication bias in ML-driven science","volume":"6","author":"Saidi","year":"2025","journal-title":"Patterns"},{"key":"ref108","doi-asserted-by":"publisher","first-page":"515","DOI":"10.3390\/toxics11060515","article-title":"The health risk and source assessment of polycyclic aromatic hydrocarbons (PAHs) in the soil of industrial cities in India","volume":"11","author":"Sankar","year":"2023","journal-title":"Toxics"},{"key":"ref109","doi-asserted-by":"publisher","first-page":"120568","DOI":"10.1016\/j.ces.2024.120568","article-title":"Hybrid modeling for improved extrapolation and transfer learning in the chemical processing industry","volume":"300","author":"Sansana","year":"2024","journal-title":"Chem. Eng. Sci."},{"key":"ref110","doi-asserted-by":"publisher","first-page":"648","DOI":"10.3390\/genes16060648","article-title":"A comprehensive review of deep learning applications with multi-omics data in Cancer research","volume":"16","author":"Sartori","year":"2025","journal-title":"Genes"},{"key":"ref111","doi-asserted-by":"publisher","first-page":"100020","DOI":"10.1016\/j.clce.2022.100020","article-title":"Recent advancements in microbial-assisted remediation strategies for toxic contaminants","volume":"2","author":"Sharma","year":"2022","journal-title":"Cleaner Chemical Engineering"},{"key":"ref112","doi-asserted-by":"publisher","first-page":"1076876","DOI":"10.3389\/fpls.2023.1076876","article-title":"Phytoremediation technologies and their mechanism for removal of heavy metal from contaminated soil: an approach for a sustainable environment","volume":"14","author":"Sharma","year":"2023","journal-title":"Front. Plant Sci."},{"key":"ref113","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.epm.2024.08.003","article-title":"Advancements in natural remediation management techniques for oil spills: challenges, innovations, and future directions","volume":"1","author":"Sharma","year":"2024","journal-title":"Environmental Pollution and Management"},{"key":"ref114","doi-asserted-by":"publisher","first-page":"343","DOI":"10.2174\/1389202921999200515140420","article-title":"Deciphering the omics of plant-microbe interaction: perspectives and new insights","volume":"21","author":"Sharma","year":"2020","journal-title":"Curr. Genomics"},{"key":"ref115","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/j.1349-7006.2004.tb03162.x","article-title":"Metabolic activation of polycyclic aromatic hydrocarbons to carcinogens by cytochromes P450 1A1 and1B1","volume":"95","author":"Shimada","year":"2004","journal-title":"Cancer Sci."},{"key":"ref116","doi-asserted-by":"publisher","first-page":"116620","DOI":"10.1016\/j.marpolbul.2024.116620","article-title":"Diversity of hydrocarbon-degrading bacteria in mangroves rhizosphere as an indicator of oil-pollution bioremediation in mangrove forests","volume":"205","author":"Siddique","year":"2024","journal-title":"Mar. Pollut. Bull."},{"key":"ref117","doi-asserted-by":"publisher","first-page":"e19296","DOI":"10.7717\/peerj.19296","article-title":"A machine-learning approach for predicting butyrate production by microbial consortia using metabolic network information","volume":"13","author":"Silva-Andrade","year":"2025","journal-title":"PeerJ"},{"key":"ref118","doi-asserted-by":"publisher","first-page":"105512","DOI":"10.1016\/j.isci.2022.105512","article-title":"Insights into the quantification and reporting of model-related uncertainty across different disciplines","volume":"25","author":"Simmonds","year":"2022","journal-title":"IScience"},{"key":"ref119","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1080\/15226514.2022.2090500","article-title":"New strategies on the application of artificial intelligence in the field of phytoremediation","volume":"25","author":"Singh","year":"2022","journal-title":"Int. J. Phytoremediation"},{"key":"ref120","volume-title":"Hydrocarbon pollution and its effect on the environment","author":"Srivastava","year":"2019"},{"key":"ref121","doi-asserted-by":"publisher","first-page":"1224","DOI":"10.3390\/pr10061224","article-title":"Bioremediation of soil from petroleum contamination","volume":"10","author":"Stepanova","year":"2022","journal-title":"PRO"},{"key":"ref122","doi-asserted-by":"publisher","first-page":"9267","DOI":"10.3390\/su13169267","article-title":"Remediation of petroleum-contaminated soils with microbial and microbial combined methods: advances, mechanisms, and challenges","volume":"13","author":"Sui","year":"2021","journal-title":"Sustainability"},{"key":"ref123","doi-asserted-by":"publisher","first-page":"11204","DOI":"10.3390\/su162411204","article-title":"Effects of oil contamination on range of soil types in middle taiga of Western Siberia","volume":"16","author":"Sutormin","year":"2024","journal-title":"Sustainability"},{"key":"ref124","doi-asserted-by":"publisher","first-page":"103043","DOI":"10.1016\/j.eti.2023.103043","article-title":"A state-of-the-art of phytoremediation approach for sustainable management of heavy metals recovery","volume":"30","author":"Tan","year":"2023","journal-title":"Environ. Technol. Innov."},{"key":"ref125","doi-asserted-by":"publisher","first-page":"513","DOI":"10.3390\/agronomy15030513","article-title":"Engineering synthetic microbial communities: diversity and applications in soil for plant resilience","volume":"15","author":"Tariq","year":"2025","journal-title":"Agronomy"},{"key":"ref126","doi-asserted-by":"publisher","first-page":"102119","DOI":"10.1016\/j.mex.2023.102119","article-title":"An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach","volume":"10","author":"Tarwidi","year":"2023","journal-title":"MethodsX"},{"key":"ref127","doi-asserted-by":"publisher","first-page":"100424","DOI":"10.1016\/j.emcon.2024.100424","article-title":"Biodegradation of polycyclic aromatic hydrocarbons: the role of ligninolytic enzymes and advances of biosensors for in-situ monitoring","volume":"11","author":"Tesfaye","year":"2025","journal-title":"Emerg. Contam."},{"key":"ref128","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1080\/713610175","article-title":"A mathematical model of phytoremediation for petroleum contaminated soil: sensitivity analysis","volume":"5","author":"Thoma","year":"2003","journal-title":"Int. J. Phytoremediation"},{"key":"ref129","doi-asserted-by":"publisher","first-page":"123389","DOI":"10.1016\/j.envres.2025.123389","article-title":"Interpretable machine learning framework for predicting pesticide phytotoxicity in wastewater reuse: integrating molecular, quantum, and experimental descriptors","volume":"289","author":"Toukak","year":"2026","journal-title":"Environ. Res."},{"key":"ref130","doi-asserted-by":"publisher","first-page":"e1007783","DOI":"10.1371\/journal.pcbi.1007783","article-title":"Deep reinforcement learning for the control of microbial co-cultures in bioreactors","volume":"16","author":"Treloar","year":"2020","journal-title":"PLoS Comput. Biol."},{"key":"ref131","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1007\/978-981-96-4824-5_16","volume-title":"Microbial Metabolomics","author":"Trivedi","year":"2025"},{"key":"ref132","doi-asserted-by":"publisher","first-page":"735","DOI":"10.3390\/plants13050735","article-title":"Phytoremediation potential of different genotypes of Salix alba and S. viminalis","volume":"13","author":"Uro\u0161evi\u0107","year":"2024","journal-title":"Plants"},{"key":"ref133","first-page":"221","volume-title":"Bioremediation of Environmental Pollutants","author":"Verma","year":"2021"},{"key":"ref134","doi-asserted-by":"publisher","first-page":"1715","DOI":"10.1007\/s00253-021-11754-5","article-title":"Identifying bioaugmentation candidates for bioremediation of polycyclic aromatic hydrocarbons in contaminated estuarine sediment of the Elizabeth River, VA, USA","volume":"106","author":"Volkoff","year":"2022","journal-title":"Appl. Microbiol. Biotechnol."},{"key":"ref135","doi-asserted-by":"publisher","first-page":"2250","DOI":"10.3390\/pr13072250","article-title":"Sustainable and advanced strategies for bioremediation of highly contaminated wastewater","volume":"13","author":"Vukovi\u0107 Domanovac","year":"2025","journal-title":"PRO"},{"key":"ref136","doi-asserted-by":"publisher","first-page":"e0340923","DOI":"10.1128\/spectrum.03409-23","article-title":"Evidence for novel polycyclic aromatic hydrocarbon degradation pathways in culturable marine isolates","volume":"12","author":"Walton","year":"2023","journal-title":"Microbiol. Spectr."},{"key":"ref137","doi-asserted-by":"publisher","first-page":"e2211613120","DOI":"10.1073\/pnas.2211613120","article-title":"Bias in machine learning models can be significantly mitigated by careful training: evidence from neuroimaging studies","volume":"120","author":"Wang","year":"2023","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref138","doi-asserted-by":"publisher","first-page":"100062","DOI":"10.1016\/j.seh.2024.100062","article-title":"Modelling phytoremediation: concepts, methods, challenges, and perspectives","volume":"2","author":"Wang","year":"2024","journal-title":"Soil Environ. Health"},{"key":"ref139","doi-asserted-by":"publisher","first-page":"144042","DOI":"10.1016\/j.jclepro.2024.144042","article-title":"Prediction of optimal bioremediation conditions for petroleum hydrocarbon contaminated soil by automated machine learning-based analysis","volume":"479","author":"Wang","year":"2024","journal-title":"J. Clean. Prod."},{"key":"ref140","doi-asserted-by":"publisher","first-page":"100017","DOI":"10.1016\/j.clce.2022.100017","article-title":"Bioprospecting culturable and unculturable microbial consortia through metagenomics for bioremediation","volume":"2","author":"Wani","year":"2022","journal-title":"Clean. Chem. Eng."},{"key":"ref141","doi-asserted-by":"publisher","first-page":"103610","DOI":"10.1016\/j.jwpe.2023.103610","article-title":"Machine learning modeling using microbiome data reveal microbial indicator for oil-contaminated groundwater","volume":"53","author":"Wijaya","year":"2023","journal-title":"J Water Process Eng"},{"key":"ref142","doi-asserted-by":"publisher","first-page":"pkaa088","DOI":"10.1093\/jncics\/pkaa088","article-title":"Proximity to oil refineries and risk of cancer: a population-based analysis","volume":"4","author":"Williams","year":"2020","journal-title":"JNCI Cancer Spectr."},{"key":"ref143","doi-asserted-by":"publisher","first-page":"678","DOI":"10.3390\/metabo12080678","article-title":"NMR and metabolomics\u2014a roadmap for the future","volume":"12","author":"Wishart","year":"2022","journal-title":"Meta"},{"key":"ref144","doi-asserted-by":"publisher","first-page":": 1189166","DOI":"10.3389\/fbioe.2023.1189166","article-title":"Machine learning: an effective technical method for future use in assessing the effectiveness of phosphorus-dissolving microbial agroremediation","volume":"11","author":"Wu","year":"2023","journal-title":"Front. Bioeng. Biotechnol."},{"key":"ref145","doi-asserted-by":"publisher","first-page":"1550346","DOI":"10.3389\/fmicb.2025.1550346","article-title":"Metagenomics-assembled genomes reveal microbial metabolic adaptation to athalassohaline environment, the case Lake Barkol, China","volume":"16","author":"Xamxidin","year":"2025","journal-title":"Front. Microbiol."},{"key":"ref146","doi-asserted-by":"publisher","first-page":"2885","DOI":"10.3389\/fmicb.2018.02885","article-title":"Petroleum hydrocarbon-degrading bacteria for the remediation of oil pollution under aerobic conditions: A perspective analysis","volume":"9","author":"Xu","year":"2018","journal-title":"Front. Microbiol."},{"key":"ref147","doi-asserted-by":"publisher","first-page":"359","DOI":"10.3389\/fpls.2020.00359","article-title":"Phytoremediation: a promising approach for revegetation of heavy metal-polluted land","volume":"11","author":"Yan","year":"2020","journal-title":"Front. Plant Sci."},{"key":"ref148","doi-asserted-by":"publisher","first-page":"D4015003","DOI":"10.1061\/(asce)hz.2153-5515.0000290","article-title":"Development of the risk assessment and management strategies for TPH-contaminated sites using TPH fraction methods","volume":"21","author":"Yang","year":"2017","journal-title":"J. Hazard. Toxic Radioact. Waste"},{"key":"ref149","doi-asserted-by":"publisher","first-page":"8360","DOI":"10.3390\/app15158360","article-title":"Application of machine learning models in optimizing wastewater treatment processes: a review","volume":"15","author":"Zamfir","year":"2025","journal-title":"Appl. Sci."},{"key":"ref150","doi-asserted-by":"publisher","first-page":"1534","DOI":"10.3390\/plants13111534","article-title":"Reducing heavy metal contamination in soil and water using phytoremediation","volume":"13","author":"Zhakypbek","year":"2024","journal-title":"Plants"},{"key":"ref151","doi-asserted-by":"publisher","first-page":"21212","DOI":"10.1021\/acs.est.3c05667","article-title":"Machine learning modeling based on microbial community for prediction of natural attenuation in groundwater","volume":"57","author":"Zhang","year":"2023","journal-title":"Environ. Sci. Technol."},{"key":"ref152","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1007\/s40820-025-02003-9","article-title":"Artificial intelligence-enhanced wearable blood pressure monitoring in resource-limited settings: a co-design of sensors, model, and deployment","volume":"18","author":"Zhang","year":"2026","journal-title":"Nano-Micro Lett."},{"key":"ref153","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.3390\/pr12061157","article-title":"Screening and optimization of soil remediation strategies assisted by machine learning","volume":"12","author":"Zhang","year":"2024","journal-title":"PRO"},{"key":"ref154","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1007\/s13205-019-2011-2","article-title":"Biodegradation of hydrocarbons by microbial strains in the presence of Ni and Pb","volume":"10","author":"Zhong","year":"2020","journal-title":"3 Biotech"}],"container-title":["Frontiers in Microbiology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2026.1742848\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T06:57:53Z","timestamp":1772693873000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2026.1742848\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,5]]},"references-count":154,"alternative-id":["10.3389\/fmicb.2026.1742848"],"URL":"https:\/\/doi.org\/10.3389\/fmicb.2026.1742848","relation":{},"ISSN":["1664-302X"],"issn-type":[{"value":"1664-302X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,5]]},"article-number":"1742848"}}