… DrugCell predictions are accurate in cell lines and also stratify clinical outcomes. Analysis of
… synergistic drug combinations, which we validate systematically by combinatorial CRISPR, …

… of cancer cell lines. These PCs were then included as covariates in a regression model for
drug sensitivity … drug response modeling in cancer: a systematic analysis with FORESEE …

… IC50 values for (a–d) bortezomib- and (e–h) cisplatin-treated MCF7, HCC38, MCF-10A,
and MDA-MB-436 breast cancer cells generated in the present study and pharmacoDB 42 …

… Resistance to monotherapy While drug response prediction can help pick an optimal …
molecular characteristics of the cancer cells, tumors often exhibit drug resistance over the course of …

… of cancer cell lines at the … cancer types by measuring drug responses [1]. As the amount of
data increases, the precise computational prediction of the drug sensitivity of cancer cell lines …

… ideal predictive model for the progression and drug sensitivity of postoperative TNBC patients.
Diverse programmed cell death (PCD) patterns play an important role in tumor … tumor cells …

… of AI-assisted methods, its main use in gastric cancer is for early detection, treatment guidance,
and prognosis prediction, which was systematically explored in the present … Methods …

… Radiation treatment: Radiation therapy kills the cancerous cells or slows down the growth
of cancerous cells by damaging their DNA. Medical experts often recommend this treatment to …

… This work presents a method to predict cancer patient drug … , this work presents the first
systematic framework to leverage … cancer cell transcriptomic signatures associated with drug …

… However, our ability to predict effective combinations is limited 4 . … To systematically identify
active drug combinations, we used the Genomics of Drug Sensitivity in Cancer (GDSC) cell …