Deciphering Cancer Genomes and Networks

NIH Director's Wednesday Afternoon Lecture Series Large-scale cancer genome sequencing consortia, such as TCGA, have provided a huge influx of somatic mutation data across large cohorts of patients. Understanding how these observed genetic alterations give rise to specific cancer phenotypes is a major aim of cancer genomics. This is challenging because numerous somatic mutations occur in each cancer genome, but only a subset are cancer-relevant; further, there is a high degree of mutational heterogeneity across individuals. Fortunately, the large and diverse biological datasets collected over the past few decades — including genome sequences across organisms and healthy individuals, protein structural data and interaction networks — provide a rich context within which to interpret cancer mutational data. In this talk, I will overview integrative computational methods my group has developed to interpret cancer mutational data, with an emphasis on identifying interactions perturbed in cancers.For more information go tohttps://oir.nih.gov/walsAir date: 2/5/2020 3:00:00 PM
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