Experts from Flinders University have forecast promising new advancements in critical DNA testing by applying machine learning to DNA profiling. A recent study has introduced a breakthrough in DNA profiling by optimising PCR with artificial intelligence (AI), applying machine learning to the process. Despite its widespread use, PCR has seen limited progress in handling degraded or low-quantity DNA samples.
The research demonstrated that AI-driven "smart PCR" systems can significantly improve DNA amplification, particularly for challenging samples that are often degraded or inhibited. By intelligently adjusting PCR cycling conditions for a wide range of sample types, the system delivers higher-quality results with faster turnaround times. This improvement is particularly important for forensic scientists who often deal with trace DNA from crime scenes, which can be difficult to analyse due to its degradation.
This new approach not only enhances forensic DNA testing but also holds promise for other fields, such as clinical diagnostics and environmental monitoring, where PCR is widely used. The study highlights the potential of AI and machine learning to revolutionise PCR testing, increasing sensitivity and accuracy while reducing errors. The advancement could lead to more reliable forensic evidence and improved outcomes in criminal investigations, particularly in cases involving compromised DNA samples.
Developing a Machine-Learning ‘Smart’ PCR Thermocycler, Part 1: Construction of a Theoretical Framework
Developing a Machine Learning ‘Smart’ Polymerase Chain Reaction Thermocycler Part 2: Putting the Theoretical Framework into Practice
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