Tag: machine learning in cancer research

An integrated machine-learning and single-cell study identifies ENTPD5 as a context-dependent candidate marker of radioresistance in hepatocellular carcinoma, with prognostic ...

An AI-driven single-cell and spatial multi-omics study defines three glioma ecosystem states and shows that a hypoxic myeloid-mesenchymal state independently ...

A machine-learning and proteomics study associates high peptide deformylase expression with immune-cold colorectal cancer, low immune infiltration, elevated oxidative phosphorylation ...

A machine-learning and cell-culture study found that shikonin induced necroptosis and apoptosis in hypoxic MDA-MB-231 breast cancer cells through a ...

A new two-step machine-learning framework called CLIMB and CLIFF computationally deconvolves bulk RNA-seq and drug sensitivity data into cell-type and ...

A machine learning framework called BioBombe maps the biological processes that cancers depend on for survival, revealing new vulnerabilities and ...

Researchers at Eindhoven University of Technology combined active learning with mechanistic logic-ODE models to uncover context-specific regulators of the immune-recruiting ...

A network toxicology and machine learning study identifies four genes through which the environmental carcinogen benzopyrene may drive prostate cancer ...

Cellular senescence has long been one of biology's most paradoxical phenomena. In healthy tissue, senescent cells—those that have permanently exited ...

In a groundbreaking advancement poised to transform cancer prognosis and treatment, researchers at Oregon Health & Science University (OHSU), funded ...