datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
protein_stability_single_mutation
Protein Data Stability - Single Mutation
This repository contains data on the change in protein stability with a single mutation.
Attribution of Data Sources
Primary Source: Tsuboyama, K., Dauparas, J., Chen, J. et al. Mega-scale experimental analysis of protein folding stability in biology and design. Nature 620, 434–444 (2023). Link to the paper
Dataset Link: Zenodo Record
As to where the dataset comes from in this broader work, the relevant dataset (#3) is shown in… See the full description on the dataset page: https://huggingface.co/datasets/Trelis/protein_stability_single_mutation.protein-sft-uniprot
protein-sft-uniprot
단백질 연구 특화 LLM 학습을 위한 SFT(Supervised Fine-Tuning) 데이터셋입니다.
UniProt 데이터베이스와 단백질 문헌에서 추출한 Q&A 형식의 대화 데이터로 구성되어 있습니다.
Dataset Summary
Total samples
1,551,711
Unique proteins
455,613
Format
JSONL (chat messages)
Size
462MB
Sources
Source
Samples
Description
UniProtQA
1,513,126
UniProt 데이터베이스에서 구조화된 단백질 정보 추출
Protein2Text-QA
38,585
단백질 관련 문헌 기반 심화 Q&A
Question Types
Type
Samples
Example… See the full description on the dataset page: https://huggingface.co/datasets/im-sangwoon/protein-sft-uniprot.gran-nanobody-proteins
GRAN Protein Structure Dataset
Dataset Description
This dataset contains protein graph data for training Graph Recurrent Attention Networks (GRAN) for protein sequence and structure generation.
Dataset Summary
Number of proteins: 2965
Average protein length: 121.0 residues
Unique amino acids: 22
Source: Nanobody protein structures
Created by: alexchilton
Date: 2025-05-04 16:01:38
Dataset Structure
Each protein entry contains:
sequence: Complete… See the full description on the dataset page: https://huggingface.co/datasets/alexchilton/gran-nanobody-proteins.tox-antitox-proteinsThis dataset is used for finetuning protGPT2. The features are ['attention_mask', 'input_ids'], no 'labels'.After using DataCollatorForLanguageModeling and DataLoader, the features will be ['attention_mask', 'input_ids', 'labels'].
protein_structure_uncertainty_auditor_v0.2Protein Structure Uncertainty Auditor
GoalDetect when predicted protein structures are too uncertain for downstream use.
Model must output
uncertainty_flag (yes/no)
uncertainty_type
recommendation
This dataset tests whether models can audit structural confidence before use in:
drug design
docking
mutation mapping
function inference
Run scorer
python scorer.py --predictions predictions.jsonl --test_csv data/test.csv