BioGAN: Enhancing Transcriptomic Data Generation with Biological Knowledge

BioGAN: Enhancing Transcriptomic Data Generation with Biological Knowledge

The advancement of computational genomics has significantly enhanced the use of data-driven solutions in disease prediction and precision medicine. Yet, challenges such as data scarcity, privacy constraints, and biases persist. Synthetic data generation offers a promising solution to these issues. H...

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Bibliographic Details
Main Authors:	Francesca Pia Panaccione, Sofia Mongardi, Marco Masseroli, Pietro Pinoli
Format:	Article
Language:	English
Published:	MDPI AG 2025-06-01
Series:	Bioengineering
Subjects:	synthetic transcriptomic data generative adversarial networks graph neural networks generative artificial intelligence biologically informed methods computational biology
Online Access:	https://www.mdpi.com/2306-5354/12/6/658
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