Advances in microbial metagenomics and artificial intelligence analysis in forensic identification

Area of Science:

• Forensic microbiology
• Metagenomics
• Bioinformatics

Background:

• Microorganisms are ubiquitous in nature and the human body, offering unique forensic identification potential.
• Advances in high-throughput sequencing and reduced costs have spurred growth in forensic microbiology and metagenomics.
• Artificial intelligence (AI) methods are increasingly valuable in forensic science for addressing complex questions.

Purpose of the Study:

• To review the current applications of microbial metagenomics in forensic science.
• To summarize the role of AI in analyzing microbial data for forensic purposes.
• To highlight key forensic areas enhanced by these technologies.

Main Methods:

• Analysis of microbial DNA through high-throughput sequencing.
• Application of AI and computational approaches for data interpretation.
• Integration of metagenomic data with forensic case studies.

Main Results:

• Microbial metagenomics and AI are effective for postmortem interval inference.
• These methods show promise for individual identification and geolocation.
• Successful application in identifying biological tissues and fluids.

Conclusions:

• Microbial metagenomics combined with AI offers powerful tools for forensic investigations.
• These technologies are advancing the field of forensic microbiology.
• Future potential exists for broader application in forensic science.