license: cc-by-4.0
pretty_name: FireProtDB
size_categories:
- 1M<n<10M
task_categories:
- other
language:
- en
tags:
- biology
- proteins
- stability
- mutation
- fireprotdb
- jsonl
FireProtDB
FireProtDB protein stability mutation dataset, normalized to newline-delimited JSON with row-level provenance.
Processed and uploaded by the MegaData post-download pipeline (internal repo). Original source: https://loschmidt.chemi.muni.cz/fireprotdb/.
Statistics
| Table files | 1 |
| Total rows | 5,465,660 |
| Total bytes | 8.48 GiB (9,105,270,725) |
Tables
| Table | Rows | Bytes |
|---|---|---|
labeled_fireprotdb_fireprotdb_search_all.jsonl.jsonl |
5,465,660 | 8.48 GiB |
Layout
.
├── _MANIFEST.json # aggregate manifest (per-table counts)
└── tables/<source_slug>.jsonl # normalized rows (one JSON object per line)
Each line in a tables/*.jsonl file is a JSON object with at least
dataset_id, row (the raw upstream row), row_index, and source_file
fields, so every row carries its upstream provenance.
Loading
hf download LiteFold/FireProtDB --repo-type dataset --local-dir ./fireprotdb
Programmatic streaming:
import json
from pathlib import Path
from huggingface_hub import snapshot_download
local = snapshot_download(repo_id="LiteFold/FireProtDB", repo_type="dataset")
for jsonl in sorted(Path(local, "tables").glob("*.jsonl")):
with jsonl.open() as f:
for line in f:
row = json.loads(line)
... # row["row"] is the upstream record
License
CC BY 4.0 (FireProtDB).
Citation
Stourac J, et al. FireProtDB: database of manually curated protein stability data. Nucleic Acids Research, 49(D1):D319-D324, 2021.
Provenance
Built from the local manifest entry fireprotdb of manifests/atlas_download_plan.json.
Pipeline source: megadata-post normalize --dataset fireprotdb --tables-only.