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ABSTRACT: Summary
The burgeoning high-throughput technologies have led to a significant surge in the scale of pharmacotranscriptomic datasets, especially for oncology. Signature search methods (SSMs), utilizing oncogenic signatures formed by differentially expressed genes through sequencing, have been instrumental in anti-cancer drug screening and identifying mechanisms of action without relying on prior knowledge. However, various studies have found that different SSMs exhibit varying performance across pharmacotranscriptomic datasets. In addition, the size of the oncogenic signature can also significantly impact the result of drug repurposing. Therefore, finding the optimal SSMs and customized oncogenic signature for a specific disease remains a challenge. To address this, we introduce Sig
SUBMITTER: Zhang J
PROVIDER: S-EPMC11398873 | biostudies-literature | 2024 Sep
REPOSITORIES: biostudies-literature