Molecular biology research progress in post-mortem interval (PMI) estimation in forensic medicine

Area of Science:

• Forensic Science
• Molecular Genetics
• Computational Biology

Background:

• Accurate post-mortem interval (PMI) estimation is critical in forensic medicine but challenging.
• Traditional PMI methods (e.g., gastric digestion, entomology) have limitations due to environmental and individual variability.
• Molecular biology offers new avenues for precise PMI determination.

Purpose of the Study:

• To review advancements in molecular biology and forensic molecular genetics for PMI estimation.
• To explore the integration of artificial intelligence (AI) and machine learning (ML) in PMI prediction.
• To provide references for improving PMI inference reliability in forensic practice.

Main Methods:

• Systematic review of molecular biology research in PMI estimation.
• Analysis of gene expression patterns for time since death.
• Application of AI and ML algorithms to multi-source forensic data.

Main Results:

• Molecular techniques, particularly gene expression analysis, show promise for accurate PMI estimation.
• AI and ML models can enhance prediction accuracy by integrating diverse data.
• These advanced methods address limitations of traditional forensic approaches.

Conclusions:

• Molecular genetics and AI represent the future of reliable PMI estimation in forensic science.
• Further research can refine these methods for practical forensic applications.
• Improved PMI accuracy aids in solving forensic cases.