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--- |
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dataset_info: |
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features: |
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- name: vh |
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dtype: string |
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- name: label |
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dtype: |
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class_label: |
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names: |
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'0': non-binder |
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'1': binder |
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splits: |
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- name: train |
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num_bytes: 177739 |
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num_examples: 1310 |
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- name: eval |
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num_bytes: 22104 |
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num_examples: 163 |
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- name: test |
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num_bytes: 22462 |
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num_examples: 163 |
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download_size: 62689 |
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dataset_size: 222305 |
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--- |
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# Human IL-6 binding dataset |
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Nanobodies binding IL-6 were obtained from the [Github repo](https://github.com/cognano/AVIDa-hIL6) for [Tsuruta et al. (2023)](https://arxiv.org/abs/2306.03329). Labels for antibody sequences were provided from the Github repo as-is. |
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Briefly, we first removed any nanobody sequence having lower than 75%; human germline sequence identity was determined using ANARCI.  |
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Among the remaining 232084 sequences, we only use antibodies that have confirmed binding to one IL-6 variant or has no binding to any IL-6 variant, leading to 211920 sequences. |
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This was de-duplicated, leading to a total of 14,467 sequences. Non-binder sequences were randomly under-sampled using [imbalanced-learn](https://github.com/scikit-learn-contrib/imbalanced-learn). |
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During stratification, we also ensure that any two sequences in the training/validation/test sets have a minimum Levenshtein distance of 1 across the CDR3 region. |
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In total there are |
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* 1310 sequences in training |
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* 163 sequences in validation |
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* 163 sequences in test. |
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| vh_full | label | |
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| ------- | ----- | |
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| EVQ... | 1 | |
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| QVQ... | 0 | |
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| EVQ... | 1 | |
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| EVK... | 0 | |
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## License |
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The data is distributed under a CC-BY-NC 4.0 license. |
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## References |
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* [AVIDA-hIL6 publication](https://arxiv.org/abs/2306.03329) |
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* [ANARCI](https://academic.oup.com/bioinformatics/article/32/2/298/1743894) |
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