README.md

---
license: mit
language:
- en
tags:
- fluorescent proteins
- biology
pretty_name: FPbase
viewer: true
configs:
- config_name: default
  data_files:
  - split: Fpbase
    path: data/fpbase_raw.csv
Citation_bibtex: |-
  @article{Lambert2019,
    title = {FPbase: a community-editable fluorescent protein database},
    volume = {16},
    ISSN = {1548-7105},
    url = {http://dx.doi.org/10.1038/s41592-019-0352-8},
    DOI = {10.1038/s41592-019-0352-8},
    number = {4},
    journal = {Nature Methods},
    publisher = {Springer Science and Business Media LLC},
    author = {Lambert,  Talley J.},
    year = {2019},
    month = mar,
    pages = {277–278}
  }
---

# FPbase: The Fluorescent Protein Database

FPbase is a free, open-source, community-editable database of fluorescent proteins and their properties, aimed at aggregating structured, searchable information useful to the imaging community and FP developers. Visit [fpbase.org](https://www.fpbase.org) for more.

This dataset updated on ,March 1st, 2026, collects FPbase fluorescent protein records (e.g., names, identifiers, sequences, and photophysical properties) for downstream analysis and modeling.

---

## Quickstart Usage

### Install HuggingFace Datasets

Each subset can be loaded into Python using the HuggingFace [`datasets`](https://huggingface.co/docs/datasets/index) library. First, install it from the command line:
```bash
pip install datasets
```

Optionally set the cache directory:
```bash
export HF_HOME=${HOME}/.cache/huggingface/
```

Then, from within Python, import the library:
```python
import datasets
```

### Load the Dataset

To load one of the `<DATASET ID>` subsets, use `datasets.load_dataset(...)`:
```python
dataset_tag = "<DATASET TAG>"
dataset = datasets.load_dataset(
    path="<HF PATH TO DATASET>",
    name=f"{dataset_tag}",
    data_dir=f"{dataset_tag}"
)["train"]
```

The dataset is loaded as a `datasets.arrow_dataset.Dataset`:
```python
>>> dataset
<RESULT OF LOADING DATASET MODEL>
```

This column-oriented format can be accessed directly, converted to a `pandas.DataFrame`, or exported to `parquet`:
```python
dataset.data.column("<COLUMN NAME IN DATASET>")
dataset.to_pandas()
dataset.to_parquet("dataset.parquet")
```

---

## Dataset Description

> Source: [github.com/tlambert03/FPbase](https://github.com/tlambert03/FPbase)

FPbase is a free and open-source, community-editable database for fluorescent proteins (FPs) and their properties. The primary objective is to aggregate structured and searchable FP data of interest to the imaging community and FP developers.

Each protein in the database has a dedicated page showing:
- Amino acid sequence
- Accession IDs (e.g. GenBank, UniProt)
- Evolution lineages and mutations
- Fluorescence attributes
- Structural data
- References that introduced or characterized the protein

Excerpts from primary literature can also be entered to store key information that is otherwise difficult to capture within the current database schema.

---

## Dataset Fields

Raw data is available at [`fpbase_raw.csv`](https://huggingface.co/datasets/RosettaCommons/FPbase/tree/main/data).

| Field | Description |
|---|---|
| `name` | Protein name |
| `fpbase_id` | ID in FPbase |
| `ex_max` | Excitation maximum |
| `em_max` | Emission maximum |
| `emhex` | Emission color (hex) |
| `exhex` | Excitation color (hex) |
| `ext_coeff` | Extinction coefficient |
| `qy` | Quantum yield |
| `lifetime_ns` | Lifetime (ns) |
| `pdb` | PDB ID |
| `genbank` | GenBank ID |
| `uniprot` | UniProt ID |
| `aggregation` | Oligomeric state |
| `switch_type` | Photo-switching type |

---
## Citation
```
@article{Lambert2019,
      title = {FPbase: a community-editable fluorescent protein database},
      volume = {16},
      ISSN = {1548-7105},
      url = {http://dx.doi.org/10.1038/s41592-019-0352-8},
      DOI = {10.1038/s41592-019-0352-8},
      number = {4},
      journal = {Nature Methods},
      publisher = {Springer Science and Business Media LLC},
      author = {Lambert,  Talley J.},
      year = {2019},
      month = mar,
      pages = {277–278}
    }
```

## Licensing

FPbase states that data in the FPbase archive are "free of all copyright restrictions" and made fully and freely available for both non-commercial and commercial use. Users should attribute the original authors of the corresponding data (referenced on the relevant protein pages).

---

## Dataset Card Authors

Yijie Luo, Ming Shen, Kaley Chinoy