ClinOmicsTrailbc
ClinOmicsTrailbc integrates clinical, (epi-)genomic, and transcriptomic data to stratify breast cancer treatments by evaluating driver mutations, tumor mutational burden, pathway activities, drug-specific biomarkers, molecular targets, pharmacogenomics, drug repositioning candidates, and immunotherapeutic options.
Key Features:
- Holistic treatment assessment: Evaluates standard-of-care targeted drugs, candidates for drug repositioning, and immunotherapeutic approaches for breast cancer.
- Multi-omics integration: Integrates clinical markers with (epi-)genomics and transcriptomics to identify driver mutations, tumor mutational burden, and core cancer-relevant pathway activity patterns.
- Biomarker and target analysis: Assesses drug-specific biomarkers, molecular drug target status, and pharmacogenomic influences to inform therapeutic selection.
Scientific Applications:
- Therapy stratification: Supports selection of personalized treatment options for breast cancer patients based on genomic and transcriptomic profiles.
- Biomarker and target discovery: Facilitates identification and evaluation of actionable driver mutations, biomarkers, and molecular drug targets.
- Translational research: Enables comparative analyses across cases to support research initiatives in breast cancer precision medicine.
Methodology:
Integration and visualization of clinical, genomic, and transcriptomic data combined with analyses of driver mutations, tumor mutational burden, pathway activities, and pharmacogenomics.
Topics
Details
- License:
- Unlicense
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- api, web application
- Operating Systems:
- Linux, Windows, Mac
- Added:
- 8/9/2019
- Last Updated:
- 11/24/2024
Operations
Publications
Schneider L, Kehl T, Thedinga K, Grammes NL, Backes C, Mohr C, Schubert B, Lenhof K, Gerstner N, Hartkopf AD, Wallwiener M, Kohlbacher O, Keller A, Meese E, Graf N, Lenhof H. ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification. Bioinformatics. 2019;35(24):5171-5181. doi:10.1093/bioinformatics/btz302. PMID:31038669. PMCID:PMC6954665.