Artificial intelligence-driven microbiome data analysis for estimation of postmortem interval and crime location

Microbial communities, demonstrating dynamic changes in cadavers and the surroundings, provide invaluable insights for forensic investigations. Conventional methodologies for microbiome sequencing data analysis face obstacles due to subjectivity and inefficiency. Artificial Intelligence (AI) present...

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Bibliographic Details
Published in:Frontiers in microbiology 2024, Vol.15, p.1334703-1334703
Main Authors: Wu, Ze, Guo, Yaoxing, Hayakawa, Miren, Yang, Wei, Lu, Yansong, Ma, Jingyi, Li, Linghui, Li, Chuntao, Liu, Yingchun, Niu, Jun
Format: Article
Language:English
Subjects:
artificial intelligence
crime location
forensic microbiology
microbiome
postmortem interval
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Summary:Microbial communities, demonstrating dynamic changes in cadavers and the surroundings, provide invaluable insights for forensic investigations. Conventional methodologies for microbiome sequencing data analysis face obstacles due to subjectivity and inefficiency. Artificial Intelligence (AI) presents an efficient and accurate tool, with the ability to autonomously process and analyze high-throughput data, and assimilate multi-omics data, encompassing metagenomics, transcriptomics, and proteomics. This facilitates accurate and efficient estimation of the postmortem interval (PMI), detection of crime location, and elucidation of microbial functionalities. This review presents an overview of microorganisms from cadavers and crime scenes, emphasizes the importance of microbiome, and summarizes the application of AI in high-throughput microbiome data processing in forensic microbiology.
ISSN:1664-302X
1664-302X
DOI:10.3389/fmicb.2024.1334703