Machine Learning Analyses Genomic data to Identify Cancer Mutations


The recent research paper from the University of Helsinki, published in Nature Communications, states a method for accurate analysis of genomics data in archival cancer biopsies.

Machine Learning methods are used in the correction of the damaged DNA to unveil the true mutation processes in tumor samples. This further aids in unlocking medicine values in millions of archival cancer samples.

The Molecular-based diagnosis supports matching the right patient with the suited cancer treatment.

The lead author Qingli Guo from the University of Helsinki, said, “This invaluable source is currently not being used for molecular diagnosis due to the poor DNA quality. Formalin causes severe damage to DNAs, which therefore place an inevitable challenge to analyse cancer genomes in preserved tissues.”

The analysis can support early detection to accurately diagnose cancer thereby unearthing the facts on some cancers becoming resistant to treatment. The new treatment can significantly boost the progress of clinical applications directly influencing the efficacy in cancer patient care.

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