Please cite the following papers when using this package:

Cremona and Chiaromonte, 2023. Probabilistic K-means with Local Alignment for Clustering and Motif Discovery in Functional Data. Journal of Computational and Graphical Statistics, 32(3), 1119-1130. Taylor & Francis.<doi:10.1080/10618600.2022.2156522>.

Di Iorio et al, 2023. funBIalign: A Hierarchical Algorithm for Functional Motif Discovery Based on Mean Squared Residue Scores. arXiv preprint arXiv:2306.04254. Available at https://arxiv.org/abs/2306.04254.

Thank you for citing our work!

Corresponding BibTeX entries:

  @Article{,
    title = {Probabilistic K-means with Local Alignment for Clustering
      and Motif Discovery in Functional Data},
    author = {Marzia A. Cremona and Francesca Chiaromonte},
    journal = {Journal of Computational and Graphical Statistics},
    volume = {32},
    number = {3},
    pages = {1119-1130},
    year = {2023},
    publisher = {Taylor & Francis},
    doi = {10.1080/10618600.2022.2156522},
    url = {https://doi.org/10.1080/10618600.2022.2156522},
  }

  @Misc{,
    title = {funBIalign: A Hierarchical Algorithm for Functional Motif
      Discovery Based on Mean Squared Residue Scores},
    author = {Jacopo {Di Iorio} and Marzia A. Cremona and Francesca
      Chiaromonte},
    year = {2023},
    eprint = {2306.04254},
    archiveprefix = {arXiv},
    primaryclass = {stat.ME},
    url = {https://arxiv.org/abs/2306.04254},
  }