---
language: dna
tags:
  - Biology
  - DNA
  - RNA
  - Splicing
license: agpl-3.0
library_name: multimolecule
---

# MaxEntScan

Maximum-entropy model for scoring short sequence motifs at RNA splice sites.

## Disclaimer

This is an UNOFFICIAL implementation of [Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals](https://doi.org/10.1089/1066527041410418) by Gene Yeo and Christopher B. Burge.

The OFFICIAL distribution of MaxEntScan is at [the Burge Lab MaxEntScan page](http://hollywood.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html).

> [!TIP]
> The MultiMolecule team has confirmed that the provided model and checkpoints are producing the same intermediate representations as the original implementation.

**The team releasing MaxEntScan did not write this model card for this model so this model card has been written by the MultiMolecule team.**

## Model Details

MaxEntScan is a maximum-entropy model for the splice donor (5') and splice acceptor (3') sequence motifs. It is **not a neural network** and has **no trainable weights**. The model parameters are fixed maximum-entropy probability tables estimated by Yeo & Burge (2004) from human splice-site sequences. MultiMolecule registers these tables as persistent buffers on the model so they serialize with saved checkpoints.

Two scorers are provided:

- `score5`: scores 5' (donor) splice sites over a 9-nucleotide window (3 exonic + 6 intronic nucleotides). The score is read from the published `me2x5` maximum-entropy probability table combined with the consensus background ratios.
- `score3`: scores 3' (acceptor) splice sites over a 23-nucleotide window. The 23-mer is decomposed into nine overlapping maximum-entropy submodels following the published maximum-entropy decomposition; the score is the log-ratio of the numerator and denominator submodel products.

### Model Specification

MaxEntScan is a parameter-free maximum-entropy model. It performs fixed table lookups and contains no learnable weights or floating-point arithmetic that the profiler can attribute to a module.

| Mode   | Window | Num Parameters (M) | FLOPs (G) | MACs (G) |
| ------ | ------ | ------------------ | --------- | -------- |
| score5 | 9      | 0.00               | 0.00      | 0.00     |
| score3 | 23     | 0.00               | 0.00      | 0.00     |

### Links

- **Code**: [multimolecule.maxentscan](https://github.com/DLS5-Omics/multimolecule/tree/master/multimolecule/models/maxentscan)
- **Paper**: [Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals](https://doi.org/10.1089/1066527041410418)
- **Developed by**: Gene Yeo, Christopher B. Burge
- **Original Distribution**: [Burge Lab MaxEntScan](http://hollywood.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html)

## Usage

The model file depends on the [`multimolecule`](https://multimolecule.danling.org) library. You can install it using pip:

```bash
pip install multimolecule
```

### Direct Use

#### 5' Splice-Site Scoring

```python
>>> import torch
>>> from multimolecule import DnaTokenizer, MaxEntScanModel, MaxEntScanConfig

>>> config = MaxEntScanConfig()
>>> model = MaxEntScanModel(config)
>>> tokenizer = DnaTokenizer.from_pretrained("multimolecule/maxentscan")
>>> # MaxEntScan scores a raw fixed-length window; do not add special tokens.
>>> input = tokenizer("CAGGTAAGT", add_special_tokens=False, return_tensors="pt")["input_ids"]
>>> output = model(input)
>>> output.logits.shape
torch.Size([1, 1])
```

#### 3' Splice-Site Scoring

```python
>>> config = MaxEntScanConfig(mode="score3")
>>> model = MaxEntScanModel(config)
>>> output = model(torch.randint(4, (1, config.window)))
>>> output.logits.shape
torch.Size([1, 1])
```

## Training Details

MaxEntScan is not trained. Its maximum-entropy probability tables were estimated once by Yeo & Burge (2004) from a set of human constitutive splice-site sequences using an iterative maximum-entropy procedure. The published tables are reused verbatim.

### Training Data

- Source: human RefSeq splice-site sequences as described in Yeo & Burge (2004).
- Maximum-entropy constraints: pairwise and higher-order positional dependencies within the splice-site window.

## Conversion And Provenance

- MaxEntScan has no upstream PyTorch checkpoint. The "parameters" are the fixed maximum-entropy probability tables (`me2x5` for the 5' scorer and the nine maximum-entropy decomposition matrices `me2x3acc1..9` for the 3' scorer; the consensus and background ratios are fixed constants from the original `score5.pl`/`score3.pl`) distributed as plain-text files with the original Yeo & Burge (2004) MaxEntScan tool.
- The original Burge-lab tables are bundled verbatim in this package as `score5_me2x5.txt` and `score3_me2x3acc.txt` (native one-float-per-line order, which equals base-4 / the published `splice5sequences` enumeration). They were obtained from the original MaxEntScan release as redistributed under the MIT license by the [`maxentpy`](https://github.com/kepbod/maxentpy) package, and are also mirrored by [Kipoi](https://github.com/kipoi/models/tree/master/MaxEntScan) (`MaxEntScan/5prime`, `MaxEntScan/3prime`); Kipoi is referenced only for provenance and is not a runtime dependency.
- `convert_checkpoint.py` builds the persistent score-table buffers directly from those bundled plain-text tables.

## Citation

```bibtex
@article{yeo2004maximum,
  author    = {Yeo, Gene and Burge, Christopher B.},
  title     = {Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals},
  journal   = {Journal of Computational Biology},
  volume    = {11},
  number    = {2-3},
  pages     = {377--394},
  year      = {2004},
  publisher = {Mary Ann Liebert, Inc.},
  doi       = {10.1089/1066527041410418}
}
```

> [!NOTE]
> The artifacts distributed in this repository are part of the MultiMolecule project.
> If you use MultiMolecule in your research, you must cite the MultiMolecule project as follows:

```bibtex
@software{chen_2024_12638419,
  author    = {Chen, Zhiyuan and Zhu, Sophia Y.},
  title     = {MultiMolecule},
  doi       = {10.5281/zenodo.12638419},
  publisher = {Zenodo},
  url       = {https://doi.org/10.5281/zenodo.12638419},
  year      = 2024,
  month     = may,
  day       = 4
}
```

## Known Limitations

- MaxEntScan only models the four canonical nucleotides `ACGT`. Unknown / `N` tokens are clamped onto `A` before table lookup.
- Inputs must be a single fixed-length window matching the configured mode (9 for `score5`, 23 for `score3`).
- The model does not accept `inputs_embeds`; it scores discrete token windows only.

## Contact

Please use GitHub issues of [MultiMolecule](https://github.com/DLS5-Omics/multimolecule/issues) for any questions or comments on the model card.

Please contact the authors of the [MaxEntScan paper](https://doi.org/10.1089/1066527041410418) for questions or comments on the paper/model.

## License

This model implementation is licensed under the [GNU Affero General Public License](license.md).

For additional terms and clarifications, please refer to our [License FAQ](license-faq.md).

```spdx
SPDX-License-Identifier: AGPL-3.0-or-later
```