Enhancing scientific discoveries in molecular biology with deep generative models | Molecular Systems Biology
Molecular generative model based on conditional variational autoencoder for de novo molecular design | Journal of Cheminformatics | Full Text
SeqMed: Recommending Medication Combination with Sequence Generative Adversarial Nets | Semantic Scholar
Inverse molecular design using machine learning: Generative models for matter engineering | Science
Neural networks to learn protein sequence–function relationships from deep mutational scanning data | PNAS
A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences - ScienceDirect
MOLER Framework. (1) First we describe the generative model. A... | Download Scientific Diagram
Protein sequence design with a learned potential | Nature Communications
Protein design and variant prediction using autoregressive generative models | Nature Communications
Comparative Study of Deep Generative Models on Chemical Space Coverage | Journal of Chemical Information and Modeling
What are Diffusion Models? | Lil'Log
Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model | Journal of Chemical Information and Modeling
Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design | DeepAI
Efficient generative modeling of protein sequences using simple autoregressive models | Nature Communications
Enhancing scientific discoveries in molecular biology with deep generative models | Molecular Systems Biology
Frontiers | Generative Models of Brain Dynamics
From lattice-protein sequence space to inferred Potts model. Protein... | Download Scientific Diagram
Deep generative models of genetic variation capture the effects of mutations | Nature Methods
Generative Adversarial Networks: Build Your First Models – Real Python
Protein sequence design with deep generative models - ScienceDirect
Deep generative models for peptide design - Digital Discovery (RSC Publishing) DOI:10.1039/D1DD00024A
The generative capacity of probabilistic protein sequence models | Nature Communications
Generative Models
