De Novo Drug Design with RNNs and Transformers
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Updated
Aug 2, 2024 - Jupyter Notebook
De Novo Drug Design with RNNs and Transformers
The official codebase of the paper "Chemical language modeling with structured state space sequence models"
Python-based GUI to collect Feedback of Chemist in Molecules
TAGMol: Target-Aware Gradient-guided Molecule Generation
HELM-GPT: de novo macrocyclic peptide design using generative pre-trained transformer
Systemic Evolutionary Chemical Space Exploration for Drug Discovery
Multi-target de novo molecular generator conditioned on AlphaFold's latent protein embeddings.
De novo drug discovery of protein-specific using Transformer Neural Network
Open source code for DyScore
Inverse Reinforcement Learning-based Structural Evolution of Small Molecules
De novo Drug Design via Binary Representations of SMILES for avoiding the Posterior Collapse Problem (BIBM 2021)
A recurrent neural network (RNN) that generates drug-like molecules for drug discovery.
Code pipeline for the PaccMann^RL in iScience: https://www.cell.com/iscience/fulltext/S2589-0042(21)00237-6
Research repo for AI aided drug discovery, de novo drug development and related topics
Code for paper on automation of discovery and synthesis of targeted molecules: https://iopscience.iop.org/article/10.1088/2632-2153/abe808
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