Researchers from IIT-Madras have developed an AI-based algorithm to differentiate and identify driver mutations from passenger mutations based on neighborhood nucleotide sequence as key discrimination features. This method was found to be highly efficient in predicting pathogenic mutations in the genome of cancer patients. A significant challenge faced in targeted therapy and precision medication for cancer treatment is the identification of 'driver’ mutations (cancer-causing mutations) from 'passenger' mutations (neutral mutations).
Recent advances in computational approaches can compare DNA sequences from cancer cells and normal cells from a large group of cancer patients and determine driver mutations and if a particular mutation was occurring more often in cancer cells than random. This frequentist approach often leads to missing out on rare driver mutations due to the complexity…
