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license: mit |
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# Dataset Description |
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Out of **20,577** human proteins (from [UniProt human proteome](https://www.uniprot.org/proteomes/UP000005640)), sequences shorter than 20 amino acids or longer than 512 amino acids were removed, resulting in a set of **12,703** proteins. The uShuffle algorithm ([python pacakge](https://github.com/guma44/ushuffle)) was then used to shuffle these protein sequences while maintaining their singlet distribution. |
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Afterwards, h-CD-HIT algorithm ([web server](http://weizhong-lab.ucsd.edu/cdhit-web-server/cgi-bin/index.cgi)) was used with three subsequent filter stages at pairwise identity cutoffs of 0.9, 0.5 and 0.1, resulting in a total of **11,698** sequences. |
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# **Citation** |
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If you use this dataset, please cite our paper: |
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``` |
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@article { |
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author = {Geffen, Yaron and Ofran, Yanay and Unger, Ron}, |
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title = {DistilProtBert: A distilled protein language model used to distinguish between real proteins and their randomly shuffled counterparts}, |
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year = {2022}, |
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doi = {10.1093/bioinformatics/btac474}, |
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URL = {https://doi.org/10.1093/bioinformatics/btac474}, |
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journal = {Bioinformatics} |
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} |
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``` |
