metadata
license: mit
language:
- en
tags:
- chemistry
- biology
size_categories:
- 1K<n<10K
Tasks
mol_und
- fg-level
fg_count.json- 100 samples across 38 different functional groups detection
ring_count.json- 20 samples, 9 types of ring unit
- scaffold-level
Murcko_scaffold.json- 40 samples, using MurckoScaffold extraction
ring_system_scaffold.json- 60 samples, extract ring system as scaffolds
- SMILES-level
equivalence.json- 50 samples, each smiles -> mutate -> permutate, mutated smiles differs from original smiles
- 50 samples, each smiles -> permutate, permutated smiles is same with original smiles
mol_edit
add.json- 20 samples, covers 10 func groups addition
delete.json- 20 samples, covers 10 func groups deletion
sub.json- 60 samples, covers 37 func groups substitution
mol_opt
drd.json- 100 samples, target-level
gsk.json- 100 samples, target-level
jnk.json- 100 samples, target-level
logp.json- 100 samples, physicochemical-level
qed.json- 100 samples, physicochemical-level
solubility.json- 100 samples, physicochemical-level
reaction
- forward reaction prediction
fs.json- 100 samples, 100 rxn-cls (each has one sample)
- (single-step) retrosynthesis prediction
retro.json- 100 samples, 100 rxn-cls (each has one sample)
- reaction condition prediction/recommendation
rcr.json- 90 samples. 10 types of reaction. Each type has 3 samples for 'Catalyst' prediction, 3 for 'Reagent' prediction and 3 for 'Solvent' prediction
- Next elementary step product prediction (NEPP)
nepp.json- given former elementary steps description, predict next elementary step's product.
- 85 rxn cls, each has 1 sample
- Mechanism Route Selection (MechSel)
mechsel.json- 100 samples
Links
- Our larger CoT dataset ChemCoTBench-CoT