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---
pretty_name: Human–Virus Protein Mistake Predictions
license: cc-by-4.0
tags:
- biology
- proteins
- classification
- viruses
- tabular
task_categories:
- tabular-classification
size_categories:
- 10K<n<100K
---
# Human–Virus Protein Mistake Predictions (Parquet)
This dataset provides **per-sequence labels, predictions, and lightweight descriptors** used in the paper:
- **Protein Language Models Expose Viral Immune Mimicry** — *Viruses* 2025, 17(9):1199.
DOI: **10.3390/v17091199** · Article: https://www.mdpi.com/1999-4915/17/9/1199
**What’s included:** a single file `HumanVirus_Protein_mistakes.parquet` with **25,117** rows and **20** columns.
**Not included:** PLM model **embeddings** (paper used Swiss-Prot T5 static embeddings or trained ESM2).
**Code:** https://github.com/ddofer/ProteinHumVir
**Workshop poster:** ICML 2024 (ML4LMS): https://openreview.net/forum?id=gGnJBLssbb
## Summary
We trained and analyzed protein language model classifiers, and interpretable tabular models in distinguishing **viral** from **human** proteins.
The dataset focuses on **DL model errors** (`mistake=True`), which are enriched for proteins implicated in **immune mimicry / immune evasion**. Use this table to reproduce error-profiling, build new classifiers, or explore biological correlates of misclassification. e.g. Explaining the mistakes of the DL/PLM models, using tabular models and explainable features, as we do in the paper.
## Schema
| column | type | brief description |
|---|---|---|
| `Sequence` | string | amino-acid sequence |
| `Length` | int | Protein sequence length |
| `virus` | int | ground truth (1=viral, 0=human) |
| `model_pred_proba_vir` | float | P(viral) |
| `model_pred_vir` | int | model prediction (1/0) |
| `mistake` | bool | prediction ≠ label |
| `Baltimore` | string? | viral group (null for human) |
| `Family` | string? | viral family |
| `Genome Composition` | string | e.g., dsDNA |
| `Genus` | string? | viral genus |
| `Keywords` | string | UniProt keywords |
| `Mass` | int | molecular mass (Da) |
| `Organism` | string | source organism |
| `Protein names` | string | protein name(s) |
| `Taxonomic lineage` | string | taxonomy path |
| `UR50_Cluster ID` | string | UniRef/UR50 ID |
| `Virus hosts` | string | known hosts |
| `av_mw` | float? | avg AA mass feature |
| `genus_human_host` | bool| Virus's genus has human host indicator |
| `human_host` | bool | Virus with human host indicator |
## Loading
**Direct (single Parquet):**
```python
from datasets import load_dataset
ds = load_dataset(
"parquet",
data_files={"train": "https://huggingface.co/datasets/<user>/<repo>/resolve/main/HumanVirus_Protein_mistakes.parquet"},
)["train"]
|