New Approaches for Decoding Cancer at the Single-Cell Level
In this webinar, Linghua Wang and Jeremy Goecks will talk about technology that enables new approaches for a better understanding of tumors on a cellular, spatial, and environmental level.
New Approaches for Decoding Cancer at the Single-Cell Level
New Approaches for Decoding Cancer at the Single-Cell Level
In this webinar, Linghua Wang and Jeremy Goecks will talk about technology that enables new approaches for a better understanding of tumors on a cellular, spatial, and environmental level.
In this webinar, Linghua Wang and Jeremy Goecks will talk about technology that enables new approaches for a better understanding of tumors on a cellular, spatial, and environmental level.
Researchers used artificial intelligence in large genomics studies to fill in gaps in patient information and improve predictions, but new research uncovers false positives and misleading correlations.
Charlene Lancaster, PhD | Jun 3, 2024 | 3 min read
An automated bioprinting and imaging platform allows researchers to examine heterogeneous responses to anticancer drugs within a tumor organoid population.
Researchers created a model that uses clinical testing data to locate the primary site of cancer cells with no known origin, likely improving survival.
Researchers integrate scRNA-seq, spatial transcriptomics, and histology imaging data to show that spatial cellular architecture predicts glioblastoma prognosis.
A study in mice finds that for certain genes, one parent’s allele can dominate expression and shape behavior—and which parent’s allele does so varies throughout the body.