HongxinXiang/ImageMol
ImageMol is a molecular image-based pre-training deep learning framework for computational drug discovery.
ImageMol helps drug discovery scientists quickly predict how new drug candidates will behave in the body, specifically their molecular properties like metabolism and toxicity, and which human proteins (targets) they might interact with. You provide images of chemical structures, and it outputs predictions about the drug's efficacy, safety, and potential targets. This is for researchers in pharmaceutical R&D or computational biology looking to accelerate early-stage drug screening.
No commits in the last 6 months.
Use this if you need to rapidly screen large numbers of chemical compounds to identify promising drug candidates by predicting their biological activity and potential side effects.
Not ideal if you are looking for a simple, off-the-shelf tool for basic molecular visualization or if you lack the computational resources and expertise to deploy deep learning models.
Stars
56
Forks
29
Language
Python
License
MIT
Category
Last pushed
Feb 27, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/HongxinXiang/ImageMol"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deepmodeling/deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
chemprop/chemprop
Message Passing Neural Networks for Molecule Property Prediction
mir-group/nequip
NequIP is a code for building E(3)-equivariant interatomic potentials
Acellera/moleculekit
MoleculeKit: Your favorite molecule manipulation kit
CederGroupHub/chgnet
Pretrained universal neural network potential for charge-informed atomistic modeling...