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