After several years of serving the research community, our ActiveDriverDB database will be retired on May 1st 2026. Please make sure to download any data you need and update your links or workflows before that date.

We want to sincerely thank all our users for their support, feedback, and collaboration over the years — your contributions have been invaluable to this project. A special thank you to Dr. Michal Krassowski for leading the development of our open-source software and database.

For any questions or assistance, please contact Jüri Reimand (juri.reimand@utoronto.ca).

You are viewing an older version (2020) of the ActiveDriverDB. To view the current (2021) version please visit activedriverdb.org

Publications

The primary publication of ActiveDriverDB:

 

ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins

Michal Krassowski, Marta Paczkowska, Kim Cullion, Tina Huang, Irakli Dzneladze, B. F. Francis Ouellette, Joseph T. Yamada, Amelie Fradet-Turcotte, Jüri Reimand

Nucleic Acids Research, gkx973, https://doi.org/10.1093/nar/gkx973

 

PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29126202

The earlier preprint of the paper is available in bioRxiv.

 

Earlier publications on systematic analyses of PTM-associated mutations in cancer, genetic disease variation and population genomics: 

  • Narayan, S., Bader, G. D. & Reimand, J. Frequent mutations in acetylation and ubiquitination sites suggest novel driver mechanisms of cancer. Genome Med 8, 55, doi:10.1186/s13073-016-0311-2 (2016).
  • Reimand, J., Wagih, O. & Bader, G. D. Evolutionary constraint and disease associations of post-translational modification sites in human genomes. PLoS Genet 11, e1004919, doi:10.1371/journal.pgen.1004919 (2015).
  • Wagih, O., Reimand, J. & Bader, G. D. MIMP: predicting the impact of mutations on kinase-substrate phosphorylation. Nat Methods 12, 531-533, doi:10.1038/nmeth.3396 (2015).
  • Reimand, J. & Bader, G. D. Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers. Molecular systems biology 9, 637, doi:10.1038/msb.2012.68 (2013).