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Machine learning algorithm brings long-read sequencing to the clinic

Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve researchers' ability to detect complex genetic alterations in cancer genomes.
Baylor College of Medicine

Integrative exome sequencing and machine learning identify new genes contributing to systemic sclerosis risk

Systemic sclerosis (SSc) is a severe autoimmune disease with complex genetic causes. Some genetic contributors have been identified, but others remain unknown, which has impeded development of ...
Science Daily

Machine learning algorithm brings long-read sequencing to the clinic

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...
GEN

Integrative Exome Sequencing and Machine Learning Identify New Genes Contributing to Systemic Sclerosis Risk

Scientists at the Baylor College of Medicine and collaborating institutions used complementary approaches that integrate exome sequencing and evolutionary action machine learning to identify protein ...
EurekAlert!

Machine learning algorithm brings long-read sequencing to the clinic

Researchers at EMBL’s European Bioinformatics Institute (EMBL-EBI) have developed a new machine learning method called SAVANA that significantly reduces sequencing errors for cancer genomes. Long-read ...