Contents Menu Expand Light mode Dark mode Auto light/dark, in light mode Auto light/dark, in dark mode Skip to content
RegVelo
RegVelo
  • About RegVelo
  • Model details
  • API
    • Datasets
      • regvelo.datasets.zebrafish_nc
      • regvelo.datasets.zebrafish_grn
      • regvelo.datasets.zebrafish_perturb
      • regvelo.datasets.murine_nc
      • regvelo.datasets.human_limb
      • regvelo.datasets.hindbrain
      • regvelo.datasets.hindbrain_grn
      • regvelo.datasets.schwann
    • Preprocessing
      • regvelo.preprocessing.preprocess_data
      • regvelo.preprocessing.set_prior_grn
      • regvelo.preprocessing.sanity_check
      • regvelo.preprocessing.filter_genes
    • Model
      • regvelo.REGVELOVI
      • regvelo.VELOVAE
      • regvelo.ModelComparison
    • Tools
      • regvelo.tools.inferred_grn
      • regvelo.tools.perturbation_effect
      • regvelo.tools.set_output
      • regvelo.tools.in_silico_block_simulation
      • regvelo.tools.in_silico_block_regulation_simulation
      • regvelo.tools.TFScanning_func
      • regvelo.tools.TFscreening
      • regvelo.tools.markov_density_simulation
      • regvelo.tools.simulated_visit_diff
      • regvelo.tools.regulation_scanning
    • Metrics
      • regvelo.metrics.abundance_test
      • regvelo.metrics.cellfate_perturbation
    • Plotting
      • regvelo.plotting.commitment_score
      • regvelo.plotting.cellfate_perturbation
      • regvelo.plotting.simulated_visit_diff
      • regvelo.plotting.regulatory_network
  • Tutorials
    • Murine neural crest development
      • Infer prior GRN from pySCENIC
      • Preprocess data and add prior GRN information
      • In-silico perturbation predictions in murine embryos (sci-RNA-seq3)
    • Zebrafish neural crest development
      • Dynamic analysis in zebrafish neural crest development
      • Screening regulatory circut via regulation perturbation
    • Model comparison with multi-view information
      • Model selection: Selecting the optimal training strategy and regularization parameter using multi-view information
    • Human limb development
      • Application: Dynamic analysis in human limb cell development
    • Human embryonic hindbrain
      • Preprocess data and add prior GRN information using a human hindbrain dataset
      • Model selection using a human hindbrain dataset
    • Mouse neural crest and schwann cells
      • Application: Model selection on mouse neural crest and schwann cell dataset
  • Release notes
    • New in 0.1.0 (2024-09-03)
  • References
Back to top

Model comparison with multi-view informationΒΆ

  • Model selection: Selecting the optimal training strategy and regularization parameter using multi-view information
Next
Model selection: Selecting the optimal training strategy and regularization parameter using multi-view information
Previous
Screening regulatory circut via regulation perturbation
Copyright © 2026, Weixu Wang.
Made with Furo