Datasets:
| license: cdla-permissive-2.0 | |
| task_categories: | |
| - tabular-regression | |
| pretty_name: true_fluorescence | |
| tags: | |
| - tabular | |
| - proteomics | |
| - regression | |
| - Biomedical | |
| - Benchmark | |
| - cds-seq | |
| configs: | |
| - config_name: true_fluorescence | |
| data_files: | |
| - split: train | |
| path: data/train.parquet | |
| - split: validation | |
| path: data/val.parquet | |
| - split: test | |
| path: data/test.parquet | |
| dataset_info: | |
| description: Sequence-level regression task predicting the log-fluorescence of higher-order | |
| mutant green fluorescent protein (avGFP) sequences. The library was generated | |
| via random mutagenesis of the wildtype sequence. Training is restricted to sequences | |
| with three or fewer mutations from parent GFP sequences; the test set contains | |
| sequences with four or more mutations, following the TAPE and PEER benchmarks. | |
| A random maximal subset of non-degenerate coding sequences was selected. Features | |
| are TF-IDF representations of amino-acid 3-mers. | |