datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Dataset-Subcellular_Localization-DeepLoc
Description
Subcellular Localization prediction is a 10-class classification task to predict where a protein locates in the cell, where each input protein x is mapped to a label y ∈ {0, 1, ..., 9}.
Splits
Protein Format: SA sequence (AF2)
The dataset is from DeepLoc: prediction of protein subcellular localization using deep learning. We employ all proteins (proteins that lack AF2 structures are removed), and split them based on 70% structure similarity (see ProteinShake)… See the full description on the dataset page: https://huggingface.co/datasets/SaProtHub/Dataset-Subcellular_Localization-DeepLoc.localization_multiRNAIf you use this dataset, please cite the paper below:
Citation:
Wang, Jun, Marc Horlacher, Lixin Cheng, and Ole Winther. ‘DeepLocRNA: An Interpretable Deep Learning Model for Predicting RNA Subcellular Localization with Domain-Specific Transfer-Learning’. Edited by Pier Luigi Martelli. Bioinformatics 40, no. 2 (1 February 2024): btae065. https://doi.org/10.1093/bioinformatics/btae065.
localizationDataset-Binary_Localization-DeepLoc
Description
Binary Localization prediction is a binary classification task where each input protein x is mapped to a label y ∈ {0, 1}, corresponding to either "membrane-bound" or "soluble" .
Protein Format: SA sequence (AF2)
Splits
The dataset is from DeepLoc: prediction of protein subcellular localization using deep learning. We employ all proteins (proteins that lack AF2 structures are removed), and split them based on 70% structure similarity (see ProteinShake), with… See the full description on the dataset page: https://huggingface.co/datasets/SaProtHub/Dataset-Binary_Localization-DeepLoc.uniprot_subcellular_localization
UniProt Subcellular Localization (Vertebrates) — ProVADA
A curated collection of vertebrate UniProt/Swiss‑Prot protein domains labeled for cytosolic and extracellular localization. We remove signal peptides, restrict domain lengths, and provide both the full set and a 30% identity‑clustered representative set with train/test/validation splits (70/20/10). This dataset underpins the subcellular localization oracle in ProVADA (preprint).
See the Files section for exact filenames and… See the full description on the dataset page: https://huggingface.co/datasets/Xiaowei0402/uniprot_subcellular_localization.m4-failure-topology-localization-v0.1What this dataset tests
Whether failures form clusters across models.
It labels failure topology:
clustered
isolated
diffuse
none
Why this exists
If failures clusterthey are predictable by neighborhood.
That beats per-model guessing.
Data format
Each row contains:
a failure type
model responses
per-model failure flags
Labels
clustered-failure
isolated-failure
diffuse-failure
no-failure
Typical clustered failures
correlation → causation
null → “ineffective”… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/m4-failure-topology-localization-v0.1.LoRNA_localizationsubcellular-localizationprotein_localization
Protein Localization Dataset
This dataset is part of the Deep Principle Bench collection.
Files
protein_localization.csv: Main dataset file
Usage
import pandas as pd
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("yhqu/protein_localization")
# Or load directly as pandas DataFrame
df = pd.read_csv("hf://datasets/yhqu/protein_localization/protein_localization.csv")
Citation
Please cite this work if you use this… See the full description on the dataset page: https://huggingface.co/datasets/yhqu/protein_localization.aviation-vibration-manifold-distortion-and-fault-localization-v0.1What this dataset tests
Whether a system can detect topological distortion
in the vibration mode manifold and localize likely damage.
It must not confuse confounders with damage:
turbulence
engine harmonics
icing
payload shifts
control surface modes.
Required outputs
distortion_pattern_type
likely_fault_location
fault_severity_estimate
localization_confidence
confounder_flags
integrity_percent_of_baseline
Scoring conventions
severity ranges 0 to 1
localization confidence ranges… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aviation-vibration-manifold-distortion-and-fault-localization-v0.1.gretelai_synthetic_text_to_sql_russian_prompts_localization
gretelai_synthetic_text_to_sql translated to russian (only SELECT queries)
Main info
This is a processed dataset gretelai/synthetic_text_to_sql with some major changes:
It contains only 3 columns: sql_prompt, sql_context, sql.
All sql-prompts were translated to russian language with utrobinmv/t5_translate_en_ru_zh_small_1024 model.
Some sql parts like filtering were translated too.
Sql-queries contain only SELECT, all TRUNCATE, DELETE, INSERT etc. were delited.
This… See the full description on the dataset page: https://huggingface.co/datasets/Tvisterious/gretelai_synthetic_text_to_sql_russian_prompts_localization.