Bengaluru: Researchers at Indian Institute of Technology (IIT)-Madras have developed a machine learning (ML) algorithm to identify personalised genes that have the potential to form and drive cancer in individuals. The model uses a'multiomic' approach, the combined study of intersectional studies that end with the suffix '-omics'. Details of the algorithm were published in a peer-reviewed paper in the journal Frontier in Genetics last month. The findings are expected to help in devising more personalised cancer therapies, contributing to the growing field of targeted therapy and immunotherapy trials. Called'Personalized Identification of driVer OGs and TSGs', or PIVOT, the model identifies personalised drivers of cancer genes and classifies them as either tumour suppressor genes (TSG) or oncogenes (OG) -- the two types of genes involved in cancer.

Bengaluru: Researchers at Indian Institute of Technology (IIT)-Madras have developed a machine learning (ML) algorithm to identify personalised …