““OMICS-Clock”: Detect Age Estimation from biological fluids and bones through Epigenomics and Transcriptomics in Crime-scene investigation”

DNA profiling based on STRs currently represents the gold standard for personal identification in forensics, but it is unable to provide information on the temporal dimension of a biological trace. The "OMICS-Clock" framework aims to bridge this critical gap by integrating epigenomics and transcriptomics to estimate chronological age and trace deposition times. Through the analysis of DNA methylation for age, RNA decay for Time since Deposition (TsD), and rhythmic genes for Time of Day (ToD), the project utilizes machine-learning models to transform multi-omic data into objective molecular timelines. This approach enhances investigations in complex scenarios, such as Disaster Victim Identification (DVI) and the analysis of degraded skeletal remains, ensuring greater evidential reliability and supporting judicial truth.