Datasets:
metadata
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.