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Integration of Gene Network Inference & Graph Neural Network

Integration of Gene Network Inference & Graph Neural Network
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Gene regulatory network inference based on ca

<p>The work provides a new clue for constructing GRNs, and&nbsp;proposed framework GRINCD also shows potential in identifying key factors affecting cancer development.</p>

Advancing gene regulatory network inference with causal discovery and graph neural networks

Gene regulatory networks (GRNs) depict the regulatory mechanisms of genes within cellular systems as a network, offering vital insights for understanding cell processes and molecular interactions that determine cellular phenotypes.

GAME-Net: a graph neural network for fast eva

Graph Neural Networks (GNN), a cutting-edge approach in artificial intelligence, can significantly improve computational calculations in heterogeneous catalysis. Researchers have made a groundbreaking development in the field of sustainable chemistry. Scientists from Tarragona (Spain) and Toronto (Canada) come up with a new tool, GAME-Net, that can make fast chemical predictions on a laptop that would otherwise have to be simulated for days by DFT on a supercomputer.

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