Mis on generatiivsed molekulimudelid?

Generative molekul models are machine learning algorithms capable of creating new molecular structures with specified properties. They are used in drug design, materials science, and bioinformatics to find promising compounds.

The main approaches include:

• Variational autoencoders (VAE), which learn to compress molecules into a latent space and generate new structures.
• Generative adversarial networks (GAN), where the generator creates molecules and the discriminator evaluates their realism.
• Graph-based models, which consider the structure of molecules as a graph of atoms and bonds.

Application in medicine accelerates the discovery of new drugs by optimizing properties such as activity, toxicity, and bioavailability. This reduces costs and time for experimental research.