References

DoseRider is a bioinformatics web tool that utilizes various resources and tools for its analyses. Below are the necessary citations for the tools and datasets used in DoseRider:

• ConsensusPathDB:
  Kamburov A, Herwig R. ConsensusPathDB 2022: molecular interactions update as a resource for network biology. Nucleic Acids Res. 2022 Jan 7;50(D1):D587-D595. doi: 10.1093/nar/gkab1128. PMID: 34850110; PMCID: PMC8728246.
• MSigDB:
  Castanza AS, Recla JM, Eby D, et al. Extending support for mouse data in the Molecular Signatures Database (MSigDB). Nat Methods 20, 1619–1620 (2023). doi: 10.1038/s41592-023-02014-7.
  Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545-50. doi: 10.1073/pnas.0506580102. Epub 2005 Sep 30. PMID: 16199517; PMCID: PMC1239896.
• MIO (Immune-Related Gene Signatures):
  Monfort-Lanzas P, Gronauer R, Madersbacher L, et al. MIO: microRNA target analysis system for immuno-oncology. Bioinformatics, Volume 38, Issue 14, July 2022, Pages 3665–3667. doi: 10.1093/bioinformatics/btac366. MIO Website
• lme4 for Statistical Analysis:
  Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1–48. doi: 10.18637/jss.v067.i01.
• Visualization Tools:
  Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016. doi: 10.1093/bioinformatics/btw313.
• Webserver Development:
  The webserver was developed using Django.

We would like to acknowledge and thank the developers of these tools for providing invaluable resources that have significantly contributed to the development of DoseRider.