Installation

BioNeuralNet supports Python 3.10 and 3.11 in this beta release. Follow the steps below to set up BioNeuralNet and its dependencies.

  1. Install BioNeuralNet via pip:

    pip install bioneuralnet

    This installs the core BioNeuralNet modules for GNN embeddings, subject representation, disease prediction (DPMON), and clustering.

  2. Install PyTorch and PyTorch Geometric (Separately):

    BioNeuralNet relies on PyTorch and PyTorch Geometric for GNN operations:

    pip install torch torchvision torchaudio
pip install torch_geometric

    For GPU-accelerated builds or other configurations visit the official sites:

    Select the appropriate build for your system (e.g., Stable, Linux, pip, Python, CPU).

    PyTorch Installation
    PyTorch Geometric Installation

  3. (Optional) Install R and External Tools:

    If you plan to use SmCCNet for network construction:

    • Install R from The R Project.

      • Version 4.4.2 or higher is recommended.

    • Install the required R packages. Open R and run:

      if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")
install.packages(c("dplyr", "jsonlite"))
BiocManager::install(c("impute", "preprocessCore", "GO.db", "AnnotationDbi"))
install.packages("SmCCNet")
install.packages("WGCNA")

  4. Additional Notes for External Tools:

    Refer to the External Tools.

  5. Next Steps: