------Under Development------
Welcome to the Biological Graph Optimiser project! This tool is designed to optimize biological graphs by improving the quality of interactions, pathways, and networks in biological datasets. Whether you are working with protein-protein interaction (PPI) graphs, gene networks, or metabolic pathways, this tool aims to streamline graph optimization for better analysis, interpretation, and prediction.
- Graph Optimisation: Optimise biological networks by refining connections based on certain metrics.
- GPU Acceleration-Leverages GPU computing (e.g. CUDA-enabled workflows) to accelerate large-scale graph operations, enabling faster optimisation for high-throughput datasets.
- FPGA Acceleration (Experimental)-Supports energy-efficient hardware acceleration using FPGAs for selected graph operations, enabling high performance with low power consumption—particularly useful for large, sparse biological graphs.
- Visualization: Visualize biological graphs using cutting-edge plotting techniques.
- Scalability: Works with small to large datasets for high-throughput analysis.
- Easy-to-Use: Simple and intuitive interface, perfect for both biologists and data scientists.
- Graph Creation: Input your biological data (e.g., protein-protein interactions, gene expression).
- Optimization Process: Apply optimization algorithms to improve the graph by refining edges, removing noise, and enhancing meaningful connections.
- Output: Visualize the optimized graph with clearly defined pathways and interactions.
To use the Biological Graph Optimiser, clone the repository and install the dependencies.
git clone https://github.com/yourusername/biological-graph-optimiser.git
cd biological-graph-optimiser
pip install -r requirements.txt