"Our approach had the benefit of sampling the same cadavers repeatedly as they decomposed and we think that this really added to the ability of our machine learning approach to see through all of the massive amount of noisy data and detect the underlying patterns," said Dr. Lents. "While we consider this a pilot study, it is a very promising proof-of-concept, and I think that microbiome-based approaches will eventually become the standard method of determining the time since death for bodies that are discovered after some time of decomposition."
"This study takes us a step further [than the human microbiome], and tells us about the necrobiome, the collection of microbes on a dead body," said Dr. Robert DeSalle, Curator of Molecular Systematics at the American Museum of Natural History, who was not affiliated with the CUNY study. "By knowing which microbes take over a dead body and how long it takes, forensic scientists might be able to use this technique to determine time of death or other aspects of a crime scene."
With additional research, this microbiome-based method promises a far more definitive method to establish time since death, which could open and close avenues of investigation in homicide cases, shed light upon possible suspects, and corroborate or disprove alibis.
Hunter R. Johnson et al. A Machine Learning Approach for Using the Postmortem Skin Microbiome to Estimate the Postmortem Interval. PLOS ONE, December 2016 DOI: 10.1371/journal.pone.0167370
Posted by Dr. Tim Sandle