CREAMMIST: an integrative probabilistic database for cancer drug response prediction.

ABSTRACT: Extensive in vitro cancer drug screening datasets have enabled scientists to identify biomarkers and develop machine learning models for predicting drug sensitivity. While most advancements have focused on omics profiles, cancer drug sensitivity scores precalculated by the original sources are often used as-is, without consideration for variabilities between studies. It is well-known that significant inconsistencies exist between the drug sensitivity scores across datasets due to differences in experimental setups and preprocessing methods used to obtain the sensitivity scores. As a result, many studies opt to focus only on a single dataset, leading to underutilization of available data and a limited interpretation of cancer pharmacogenomics analysis. To overcome these caveats, we have dev

SUBMITTER: Yingtaweesittikul H 

PROVIDER: S-EPMC9825458 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature