Citation

If you use PhosphoVelocity in your research, please cite the software package itself, as well as the foundational methodological papers that describe the mathematical models and network priors used in this pipeline.

Citing the Software

To cite the PhosphoVelocity software and pipeline, please use the following:

Plain Text:

Mishra, A. (2026). PhosphoVelocity: A Bayesian phosphosite velocity modeling pipeline [Computer software]. https://github.com/bibymaths/phospho-velocity

BibTeX:

@software{PhosphoVelocity2026,
  author = {Mishra, Abhinav},
  title = {PhosphoVelocity: A Bayesian phosphosite velocity modeling pipeline},
  year = {2026},
  url = {[https://github.com/bibymaths/phospho-velocity](https://github.com/bibymaths/phospho-velocity)},
  note = {Computer software}
}

---

Citing the Methodologies

PhosphoVelocity builds upon several key methodologies for Bayesian modeling, log-ratio uncertainty, and kinase-substrate network inference. Please cite the relevant papers below depending on which features of the pipeline you utilize.

1. Peptide Log-Ratio Uncertainty Model

This paper describes the probability-based detection of phosphoproteomic uncertainty incorporated into our observation model.

Robin, X., Voellmy, F., Ferkinghoff-Borg, J., Howard, C., Altenburg, T., Engel, M., Simpson, C. D., Saginc, G., Koplev, S., Klipp, E., Longden, J., & Linding, R. (2019). Probability-based detection of phosphoproteomic uncertainty reveals rare signaling events driven by oncogenic kinase gene fusion. Systems Biology. https://doi.org/10.1101/621961

@article{Robin2019,
  title={Probability-based detection of phosphoproteomic uncertainty reveals rare signaling events driven by oncogenic kinase gene fusion},
  author={Robin, X. and Voellmy, F. and Ferkinghoff-Borg, J. and Howard, C. and Altenburg, T. and Engel, M. and Simpson, C. D. and Saginc, G. and Koplev, S. and Klipp, E. and Longden, J. and Linding, R.},
  journal={Systems Biology},
  year={2019},
  doi={10.1101/621961}
}

2. Kinase–Substrate Network Inference

These papers detail the foundation of the kinase-substrate network priors (KinomeXplorer / NetworKIN) used for regularization.

Creixell, P., Palmeri, A., Miller, C. J., Lou, H. J., Santini, C. C., Nielsen, M., Turk, B. E., & Linding, R. (2015). Unmasking Determinants of Specificity in the Human Kinome. Cell, 163(1), 187–201. https://doi.org/10.1016/j.cell.2015.08.057

@article{Creixell2015Specificity,
  title={Unmasking Determinants of Specificity in the Human Kinome},
  author={Creixell, P. and Palmeri, A. and Miller, C. J. and Lou, H. J. and Santini, C. C. and Nielsen, M. and Turk, B. E. and Linding, R.},
  journal={Cell},
  volume={163},
  number={1},
  pages={187--201},
  year={2015},
  doi={10.1016/j.cell.2015.08.057}
}

Creixell, P., Schoof, E. M., Simpson, C. D., Longden, J., Miller, C. J., Lou, H. J., Perryman, L., Cox, T. R., Zivanovic, N., Palmeri, A., Wesolowska-Andersen, A., Helmer-Citterich, M., Ferkinghoff-Borg, J., Itamochi, H., Bodenmiller, B., Erler, J. T., Turk, B. E., & Linding, R. (2015). Kinome-wide Decoding of Network-Attacking Mutations Rewiring Cancer Signaling. Cell, 163(1), 202–217. https://doi.org/10.1016/j.cell.2015.08.056

@article{Creixell2015Mutations,
  title={Kinome-wide Decoding of Network-Attacking Mutations Rewiring Cancer Signaling},
  author={Creixell, P. and Schoof, E. M. and Simpson, C. D. and Longden, J. and Miller, C. J. and Lou, H. J. and Perryman, L. and Cox, T. R. and Zivanovic, N. and Palmeri, A. and Wesolowska-Andersen, A. and Helmer-Citterich, M. and Ferkinghoff-Borg, J. and Itamochi, H. and Bodenmiller, B. and Erler, J. T. and Turk, B. E. and Linding, R.},
  journal={Cell},
  volume={163},
  number={1},
  pages={202--217},
  year={2015},
  doi={10.1016/j.cell.2015.08.056}
}

3. Bayesian Velocity Modeling Foundation

This paper establishes the earlier Bayesian framework for velocity modeling that inspired the temporal trajectory reconstruction in this package.

Engel, M., Longden, J., Ferkinghoff-Borg, J., Robin, X., Saginc, G., & Linding, R. (2018). Bowhead: Bayesian modelling of cell velocity during concerted cell migration. PLOS Computational Biology, 14(1), e1005900. https://doi.org/10.1371/journal.pcbi.1005900

@article{Engel2018,
  title={Bowhead: Bayesian modelling of cell velocity during concerted cell migration},
  author={Engel, M. and Longden, J. and Ferkinghoff-Borg, J. and Robin, X. and Saginc, G. and Linding, R.},
  journal={PLOS Computational Biology},
  volume={14},
  number={1},
  pages={e1005900},
  year={2018},
  doi={10.1371/journal.pcbi.1005900}
}