News Summary

• Developing software to reveal large genetic changes that lead to cancer most genetic testing of cancer cells focuses on individual point mutations.
• Mikhail Kolmogorov is developing computational methods to find these structural variations in biological data.
• His work may soon translate to cancer clinics, where an algorithm can detect structural variations that may drive as many as half of all cancers.
• Better genomics testing would enable oncologists to perform more accurate risk assessments and formulate targeted treatments.
• that means algorithms like Severus could be literal lifesavers for the youngest cancer patients.
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