Cecere, F. (2024). scGraphVerse: A Gene Regulatory Network Analysis Package. R package version 0.99.0. URL: https://ngsFC.github.io/scGraphVerse

Park, B., Choi, H., & Park, C. (2021). Zero-inflated latent Gaussian mixture models for inference of gene regulatory networks. Bioinformatics, 37(18), 3085-3092.<doi:10.1093/bioinformatics/btab293>

Petralia, F., Wang, P., Yang, J., & Tu, Z. (2015). Integrative random forest for gene regulatory network inference. Bioinformatics, 31(12), i197-i205.<doi:10.1093/bioinformatics/btv268>

Policastro, V., Righelli, D., Carissimo, A., & Cutillo, L. (2021). A new consensus-based method for biomarker discovery from networks. BMC Bioinformatics, 22, 1-18.<doi:10.1186/s12859-021-04441-8>

Corresponding BibTeX entries:

  @Manual{,
    title = {scGraphVerse: A Gene Regulatory Network Analysis Package},
    author = {Francesco Cecere},
    year = {2024},
    note = {R package version 0.99.0},
    url = {https://ngsFC.github.io/scGraphVerse},
  }

  @Article{,
    title = {Zero-inflated latent Gaussian mixture models for inference
      of gene regulatory networks},
    author = {Beomjin Park and Hosik Choi and Changyi Park},
    journal = {Bioinformatics},
    year = {2021},
    volume = {37},
    pages = {3085-3092},
    doi = {10.1093/bioinformatics/btab293},
  }

  @Article{,
    title = {Integrative random forest for gene regulatory network
      inference},
    author = {Francesca Petralia and Pei Wang and Jiayu Yang and
      Zhidong Tu},
    journal = {Bioinformatics},
    year = {2015},
    volume = {31},
    pages = {i197-i205},
    doi = {10.1093/bioinformatics/btv268},
  }

  @Article{,
    title = {A new consensus-based method for biomarker discovery from
      networks},
    author = {Valeria Policastro and Dario Righelli and Annamaria
      Carissimo and Luisa Cutillo},
    journal = {BMC Bioinformatics},
    year = {2021},
    volume = {22},
    pages = {1-18},
    doi = {10.1186/s12859-021-04441-8},
  }