Datasets:
metadata
license: cdla-permissive-2.0
task_categories:
- tabular-regression
pretty_name: true_melting_point
tags:
- tabular
- proteomics
- regression
- Biomedical
- Benchmark
- cds-seq
configs:
- config_name: true_melting_point
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 melting temperature of
proteins. Data originates from the Thermostability Atlas, compiled via a
mass spectrometry-based proteomic approach. Splits follow the 'mixed'
strategy from FLIP: sequences are clustered at 20% identity, with 80% of
clusters assigned to train and 20% to test, avoiding over-emphasis of large
clusters. Features are mean-pooled ESM-2 (esm2_t12_35M_UR50D) sequence
embeddings.