Datasets:
__key__
stringclasses 1
value | __url__
stringclasses 1
value | csv
unknown |
|---|---|---|
allmolgen | "/tmp/hf-datasets-cache/medium/datasets/56139507531075-config-parquet-and-info-Pixelatory-AllMolGen-(...TRUNCATED) | "c21pbGVzLHNtaV9sZW4KTkMoPU8pQ09jMWNjY2MoTkMoPU8pYzJjbmMzY2NjY2MzbjIpYzEsMzgKQ0MxQ04oQyg9TylDT2MyY2N(...TRUNCATED) |
Downloaded using PyTDC (https://tdcommons.ai/).
Contains the unique canonicalized SMILES molecules from MOSES, ZINC-250K, and ChEMBL-29, done with RDKit.
Distribution of tokenized SMILES sequence lengths below. The following regex string was used to split the SMILES molecule into tokens: ([[^]]+]|Br?|Cl?|N|O|S|P|F|I|b|c|n|o|s|p|(|)|.|=|#|-|+|\|/|:|~|@|?|>>?|*|$|%[0-9]{2}|[0-9])
Included in the .csv (after extracting the .tar.xz file) is a column "smi_len".
If using the same SMILES tokenization regex string as above, you can simply filter using the values in this column ("smi_len").
I'd recommend post-processing since clearly a majority of the sequences are of a much shorter length than the highest, which is above 1400 (using my regex string).- Downloads last month
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