TEMPO: A Hybrid-Neuromorphic Pipeline for Efficient Multi-Omic High-Dimensional Oncology Data Integration
Project description
TEMPO: A Hybrid-Neuromorphic Pipeline for Efficient Multi-Omic Cancer Data Integration
TEMPO is a professional-grade, energy-efficient Python package designed for multi-omic cancer data integraton. Using an innovative hybrid ANN-SNN hybrid model and advanced features, TEMPO has drastically reduces computational overhead (Synaptic Operations and FLOPs) while maintaining state-of-the-art classification performance on highly imbalanced pan-cancer datasets.
Key Features
- Multi-Omic Integration: Seamlessly aligns disparate modalities (e.g., mRNA expression, Proteomics, CNV, Clinical data).
- Neuromorphic Efficiency: Leverages Leaky Integrate-and-Fire (LIF) neurons to minimize computational power.
- Smart Routing & Gating: Implements Gumbel-Softmax modality routing and Fast Fourier Transform (FFT) semantic addressing.
- Scikit-Learn Style API: Clean, intuitive
.fit()and.predict()wrapper built over PyTorch execution blocks. - Imbalance-Aware: Built-in balanced Focal Loss and automated sample weighting to handle rare cancer subtypes.
Installation
To install TEMPO locally in editable development mode, navigate to your root package directory and run:
pip install -e .
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