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A framework for analyzing biological data via graph construction, clustering, and embedding generation. The resulting embeddings power downstream tasks like disease prediction, subject representati…
This repository contains the code and supplementary material for the paper "Learning from Multi-omics Networks to Enhance Disease Prediction using Graph Neural Networks", accepted at IEEE BIBM 2024…
From-scratch implementations of MLP, CNN, RNN, and LSTM using only Python standard libraries. No NumPy, no frameworks, just raw lists and loops. Fully functional and great for learning.