Computational Chemistry

SubGrapher creates molecular fingerprints from images via functional group segmentation, enabling retrieval without full …...

A micro-review of Optical Chemical Structure Recognition (OCSR), from rule-based systems to modern AI models.

αExtractor uses ResNet-Transformer to extract chemical structures from literature images, including noisy and hand-drawn …...

Fujiyoshi et al.'s segment-based approach for recognizing chemical structures in challenging Japanese patent images with …...

Clevert et al.'s two-stage CNN approach for converting molecular images to SMILES using CDDD embeddings and extensive …...

Chen et al.'s dual-stream encoder approach for robust molecular structure recognition from diverse real-world images …...

Filippov & Nicklaus's open-source rule-based system for converting molecular structure images into machine-readable …...

MolParser converts molecular images from scientific documents to machine-readable formats using E-SMILES....

ZINC-22 dataset card covering 37+ billion make-on-demand molecules for virtual screening and drug discovery.

Visualize SELFIES molecular representations and test their 100% robustness through random sampling experiments.

Learn how to create 2D molecular images from SMILES strings using RDKit and PIL, with proper formatting and legends.

SELFIES is a 100% robust molecular string representation for ML, implemented in the open-source selfies Python library....