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Most cancer types analyzed harbored one or more subclonal populations, which could pose a clinical challenge, the researchers said.
A combination of whole-blood gene expression, splicing, and demographic data could predict the tissue-specific expression of about 60 percent of genes.
Starting with genome sequences for thousands of individuals from Alzheimer's-affected families, researchers found rare disease-associated variants at 13 new loci.
The approach applies deep learning and could potentially be used to identify people with early-stage disease when therapies may have more of an effect.
Under their 10-year partnership, IBM will install an early instance of its Quantum System One at Cleveland Clinic to promote AI-driven life sciences discovery.