--- datasets: - multimolecule/gencode library_name: multimolecule license: agpl-3.0 pipeline: splice-site pipeline_tag: other tags: - Biology - RNA - Splicing - rna widget: - example_title: microRNA 21 pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: UAGCUUAUCAGACUGAUGUUGA - example_title: microRNA 146a pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: UGAGAACUGAAUUCCAUGGGUU - example_title: microRNA 155 pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: UUAAUGCUAAUCGUGAUAGGGGUU - example_title: RNA component of mitochondrial RNA processing endoribonuclease pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: GGUUCGUGCUGAAGGCCUGUAUCCUAGGCUACACACUGAGGACUCUGUUCCUCCCCUUUCCGCCUAGGGGAAAGUCCCCGGACCUCGGGCAGAGAGUGCCACGUGCAUACGCACGUAGACAUUCCCCGCUUCCCACUCCAAAGUCCGCCAAGAAGCGUAUCCCGCUGAGCGGCGUGGCGCGGGGGCGUCAUCCGUCAGCUCCCUCUAGUUACGCAGGCAGUGCGUGUCCGCGCACCAACCACACGGGGCUCAUUCUCAGCGCGGCUGUAAAAAAAAA - example_title: 7SK small nuclear RNA pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: GGAUGUGAGGGCGAUCUGGCUGCGACAUCUGUCACCCCAUUGAUCGCCAGGGUUGAUUCGGCUGAUCUGGCUGGCUAGGCGGGUGUCCCCUUCCUCCCUCACCGCUCCAUGUGCGUCCCUCCCGAAGCUGCGCGCUCGGUCGAAGAGGACGACCAUCCCCGAUAGAGGAGGACCGGUCUUCGGUCAAGGGUAUACGAGUAGCUGCGCUCCCCUGCUAGAACCUCCAAACAAGCUCUCAAGGUCCAUUUGUAGGAGAACGUAGGGUAGUCAAGCUUCCAAGACUCCAGACACAUCCAAAUGAGGCGCUGCAUGUGGCAGUCUGCCUUUCUUUU - example_title: telomerase RNA component pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: GGGUUGCGGAGGGUGGGCCUGGGAGGGGUGGUGGCCAUUUUUUGUCUAACCCUAACUGAGAAGGGCGUAGGCGCCGUGCUUUUGCUCCCCGCGCGCUGUUUUUCUCGCUGACUUUCAGCGGGCGGAAAAGCCUCGGCCUGCCGCCUUCCACCGUUCAUUCUAGAGCAAACAAAAAAUGUCAGCUGCUGGCCCGUUCGCCCCUCCCGGGGACCUGCGGCGGGUCGCCUGCCCAGCCCCCGAACCCCGCCUGGAGGCCGCGGUCGGCCCGGGGCUUCUCCGGAGGCACCCACUGCCACCGCGAAGAGUUGGGCUCUGUCAGCCGCGGGUCUCUCGGGGGCGAGGGCGAGGUUCAGGCCUUUCAGGCCGCAGGAAGAGGAACGGAGCGAGUCCCCGCGCGCGGCGCGAUUCCCUGAGCUGUGGGACGUGCACCCAGGACUCGGCUCACACAUGC - example_title: vault RNA 2-1 pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: CGGGUCGGAGUUAGCUCAAGCGGUUACCUCCUCAUGCCGGACUUUCUAUCUGUCCAUCUCUGUGCUGGGGUUCGAGACCCGCGGGUGCUUACUGACCCUUUUAUGCAA - example_title: brain cytoplasmic RNA 1 pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: GGCCGGGCGCGGUGGCUCACGCCUGUAAUCCCAGCUCUCAGGGAGGCUAAGAGGCGGGAGGAUAGCUUGAGCCCAGGAGUUCGAGACCUGCCUGGGCAAUAUAGCGAGACCCCGUUCUCCAGAAAAAGGAAAAAAAAAAACAAAAGACAAAAAAAAAAUAAGCGUAACUUCCCUCAAAGCAACAACCCCCCCCCCCCUUU - example_title: HIV-1 TAR-WT pipeline_tag: splice-site sequence_type: ncRNA task: splice-site text: GGUCUCUCUGGUUAGACCAGAUCUGAGCCUGGGAGCUCUCUGGCUAACUAGGGAACC - example_title: prion protein (Kanno blood group) pipeline_tag: splice-site sequence_type: mRNA task: splice-site text: AUGGCGAACCUUGGCUGCUGGAUGCUGGUUCUCUUUGUGGCCACAUGGAGUGACCUGGGCCUCUGC - example_title: interleukin 10 pipeline_tag: splice-site sequence_type: mRNA task: splice-site text: AUGCACAGCUCAGCACUGCUCUGUUGCCUGGUCCUCCUGACUGGGGUGAGGGCC - example_title: Zaire ebolavirus pipeline_tag: splice-site sequence_type: mRNA task: splice-site text: AAUGUUCAAACACUUUGUGAAGCUCUGUUAGCUGAUGGUCUUGCUAAAGCAUUUCCUAGCAAUAUGAUGGUAGUCACAGAGCGUGAGCAAAAAGAAAGCUUAUUGCAUCAAGCAUCAUGGCACCACACAAGUGAUGAUUUUGGUGAGCAUGCCACAGUUAGAGGGAGUAGCUUUGUAACUGAUUUAGAGAAAUACAAUCUUGCAUUUAGAUAUGAGUUUACAGCACCUUUUAUAGAAUAUUGUAACCGUUGCUAUGGUGUUAAGAAUGUUUUUAAUUGGAUGCAUUAUACAAUCCCACAGUGUUAU - example_title: SARS coronavirus pipeline_tag: splice-site sequence_type: mRNA task: splice-site text: AUGUUUAUUUUCUUAUUAUUUCUUACUCUCACUAGUGGUAGUGACCUUGACCGGUGCACCACUUUUGAUGAUGUUCAAGCUCCUAAUUACACUCAACAUACUUCAUCUAUGAGGGGGGUUUACUAUCCUGAUGAAAUUUUUAGAUCAGACACUCUUUAUUUAACUCAGGAUUUAUUUCUUCCAUUUUAUUCUAAUGUUACAGGGUUUCAUACUAUUAAUCAUACGUUUGACAACCCUGUCAUACCUUUUAAGGAUGGUAUUUAUUUUGCUGCCACAGAGAAAUCAAAUGUUGUCCGUGGUUGGGUUUUUGGUUCUACCAUGAACAACAAGUCACAGUCGGUGAUUAUUAUUAACAAUUCUACUAAUGUUGUUAUACGAGCAUGUAACUUUGAAUUGUGUGACAACCCUUUCUUUGCUGUUUCUAAACCCAUGGGUACACAGACACAUACUAUGAUAUUCGAUAAUGCAUUUAAAUGCACUUUCGAGUACAUAUCU - example_title: insulin pipeline_tag: splice-site sequence_type: mRNA task: splice-site text: AUGGCCCUGUGGAUGCGCCUCCUGCCCCUGCUGGCGCUGCUGGCCCUCUGGGGACCUGACCCAGCCGCAGCCUUUGUGAACCAACACCUGUGCGGCUCACACCUGGUGGAAGCUCUCUACCUAGUGUGCGGGGAACGAGGCUUCUUCUACACACCCAAGACCCGCCGGGAGGCAGAGGACCUGCAGGUGGGGCAGGUGGAGCUGGGCGGGGGCCCUGGUGCAGGCAGCCUGCAGCCCUUGGCCCUGGAGGGGUCCCUGCAGAAGCGUGGCAUUGUGGAACAAUGCUGUACCAGCAUCUGCUCCCUCUACCAGCUGGAGAACUACUGCAACUAG - example_title: cyclin dependent kinase inhibitor 2A pipeline_tag: splice-site sequence_type: mRNA task: splice-site text: AUGGAGCCGGCGGCGGGGAGCAGCAUGGAGCCUUCGGCUGACUGGCUGGCCACGGCCGCGGCCCGGGGUCGGGUAGAGGAGGUGCGGGCGCUGCUGGAGGCGGGGGCGCUGCCCAACGCACCGAAUAGUUACGGUCGGAGGCCGAUCCAGGUCAUGAUGAUGGGCAGCGCCCGAGUGGCGGAGCUGCUGCUGCUCCACGGCGCGGAGCCCAACUGCGCCGACCCCGCCACUCUCACCCGACCCGUGCACGACGCUGCCCGGGAGGGCUUCCUGGACACGCUGGUGGUGCUGCACCGGGCCGGGGCGCGGCUGGACGUGCGCGAUGCCUGGGGCCGUCUGCCCGUGGACCUGGCUGAGGAGCUGGGCCAUCGCGAUGUCGCACGGUACCUGCGCGCGGCUGCGGGGGGCACCAGAGGCAGUAACCAUGCCCGCAUAGAUGCCGCGGAAGGUCCCUCAGACAUCCCCGAUUGA - example_title: human papillomavirus type 16 E6 pipeline_tag: splice-site sequence_type: mRNA task: splice-site text: AUGCACCAAAAGAGAACUGCAAUGUUUCAGGACCCACAGGAGCGACCCAGAAAGUUACCACAGUUAUGCACAGAGCUGCAAACAACUAUACAUGAUAUAAUAUUAGAAUGUGUGUACUGCAAGCAACAGUUACUGCGACGUGAGGUAUAUGACUUUGCUUUUCGGGAUUUAUGCAUAGUAUAUAGAGAUGGGAAUCCAUAUGCUGUAUGUGAUAAAUGUUUAAAGUUUUAUUCUAAAAUUAGUGAGUAUAGACAUUAUUGUUAUAGUUUGUAUGGAACAACAUUAGAACAGCAAUACAACAAACCGUUGUGUGAUUUGUUAAUUAGGUGUAUUAACUGUCAAAAGCCACUGUGUCCUGAAGAAAAGCAAAGACAUCUGGACAAAAAGCAAAGAUUCCAUAAUAUAAGGGGUCGGUGGACCGGUCGAUGUAUGUCUUGUUGCAGAUCAUCAAGAACACGUAGAGAAACCCAGCUGUAA - example_title: NRAS proto-oncogene pipeline_tag: splice-site sequence_type: 5' UTR task: splice-site text: GGGGCCGGAAGUGCCGCUCCUUGGUGGGGGCUGUUCAUGGCGGUUCCGGGGUCUCCAACAUUUUUCCCGGCUGUGGUCCUAAAUCUGUCCAAAGCAGAGGCAGUGGAGCUUGAGGUUCUUGCUGGUGUGAA - example_title: amyloid beta precursor protein pipeline_tag: splice-site sequence_type: 5' UTR task: splice-site text: GUCAGUUUCCUCGGCAGCGGUAGGCGAGAGCACGCGGAGGAGCGUGCGCGGGGGCCCCGGGAGACGGCGGCGGUGGCGGCGCGGGCAGAGCAAGGACGCGGCGGAUCCCACUCGCACAGCAGCGCACUCGGUGCCCCGCGCAGGGUCGCG - example_title: RUNX family transcription factor 1 pipeline_tag: splice-site sequence_type: 5' UTR task: splice-site text: ACUUCUUUGGGCCUCAUAAACAACCACAGAACCACAAGUUGGGUAGCCUGGCAGUGUCAGAAGUCUGAACCCAGCAUAGUGGUCAGCAGGCAGGACGAAUCACACUGAAUGCAAACCACAGGGUUUCGCAGCGUGGUAAAAGAAAUCAUUGAGUCCCCCGCCUUCAGAAGAGGGUGCAUUUUCAGGAGGAAGCG - example_title: fragile X messenger ribonucleoprotein 1 pipeline_tag: splice-site sequence_type: 5' UTR task: splice-site text: CUCAGUCAGGCGCUCAGCUCCGUUUCGGUUUCACUUCCGGUGGAGGGCCGCCUCUGAGCGGGCGGCGGGCCGACGGCGAGCGCGGGCGGCGGCGGUGACGGAGGCGCCGCUGCCAGGGGGCGUGCGGCAGCGCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGAGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCUGGGCCUCGAGCGCCCGCAGCCCACCUCUCGGGGGCGGGCUCCCGGCGCUAGCAGGGCUGAAGAGAAG - example_title: MYC proto-oncogene pipeline_tag: splice-site sequence_type: 5' UTR task: splice-site text: AACUCGCUGUAGUAAUUCCAGCGAGAGGCAGAGGGAGCGAGCGGGCGGCCGGCUAGGGUGGAAGAGCCGGGCGAGCAGAGCUGCGCUGCGGGCGUCCUGGGAAGGGAGAUCCGGAGCGAAUAGGGGGCUUCGCCUCUGGCCCAGCCCUCCCGCUGAUCCCCCAGCCAGCGGUCCGCAACCCUUGCCGCAUCCACGAAACUUUGCCCAUAGCAGCGGGCGGGCACUUUGCACUGGAACUUACAACACCCGAGCAAGGACGCGACUCUCCCGACGCGGGGAGGCUAUUCUGCCCAUUUGGGGACACUUCCCCGCCGCUGCCAGGACCCGCUUCUCUGAAAGGCUCUCCUUGCAGCUGCUUAGACG - example_title: activating transcription factor 4 pipeline_tag: splice-site sequence_type: 5' UTR task: splice-site text: CAUUUCUACUUUGCCCGCCCACAGAUGUAGUUUUCUCUGCGCGUGUGCGUUUUCCCUCCUCCCCGCCCUCAGGGUCCACGGCCACCAUGGCGUAUUAGGGGCAGCAGUGCCUGCGGCAGCAUUGGCCUUUGCAGCGGCGGCAGCAGCACCAGGCUCUGCAGCGGCAACCCCCAGCGGCUUAAGCCAUGGCGCUUCUCACGGCAUUCAGCAGCAGCGUUGCUGUAACCGACAAAGACACCUUCGAAUUAAGCACAUUCCUCGAUUCCAGCAAAGCACCGCAAC - example_title: Human GPI protein p137 pipeline_tag: splice-site sequence_type: 3' UTR task: splice-site text: UUUUUAAAAGGAAAAGAUACCAAAUGCCUGCUGCUACCACCCUUUUCAAUUGCUAUGUUUUGAAAGGCACCAGUAUGUGUUUUAGAUUGAUUUAAAUGUUUCAUUUAAAUCACGGACAGUAGUUUCAGUUCUGAUGGUAUAAGCAAAACAAAUAAAACGUUUAUAAAAGUUGUAUCUUGAAACACUGGUGUUCAACAGCUAGCAGCUUAUGUGAUUCACCCCAUGCCACGUUAGUGUCACAAAUUUUAUGGUUUAUCUCCAGCAACAUUUCUCUAGUACUUGCACUUAUUAUCUGAAUUC - example_title: nucleophosmin 1 pipeline_tag: splice-site sequence_type: 3' UTR task: splice-site text: GAAAAUAGUUUAAACAAUUUGUUAAAAAAUUUUCCGUCUUAUUUCAUUUCUGUAACAGUUGAUAUCUGGCUGUCCUUUUUAUAAUGCAGAGUGAGAACUUUCCCUACCGUGUUUGAUAAAUGUUGUCCAGGUUCUAUUGCCAAGAAUGUGUUGUCCAAAAUGCCUGUUUAGUUUUUAAAGAUGGAACUCCACCCUUUGCUUGGUUUUAAGUAUGUAUGGAAUGUUAUGAUAGGACAUAGUAGUAGCGGUGGUCAGACAUGGAAAUGGUGGGGAGACAAAAAUAUACAUGUGAAAUAAAACUCAGUAUUUUAAUAAAGUAGCACGGUUUCUAUUGA - example_title: superoxide dismutase 1 pipeline_tag: splice-site sequence_type: 3' UTR task: splice-site text: ACAUUCCCUUGGAUGUAGUCUGAGGCCCCUUAACUCAUCUGUUAUCCUGCUAGCUGUAGAAAUGUAUCCUGAUAAACAUUAAACACUGUAAUCUUAAAAGUGUAAUUGUGUGACUUUUUCAGAGUUGCUUUAAAGUACCUGUAGUGAGAAACUGAUUUAUGAUCACUUGGAAGAUUUGUAUAGUUUUAUAAAACUCAGUUAAAAUGUCUGUUUCAAUGACCUGUAUUUUGCCAGACUUAAAUCACAGAUGGGUAUUAAACUUGUCAGAAUUUCUUUGUCAUUCAAGCCUGUGAAUAAAAACCCUGUAUGGCACUUAUUAUGAGGCUAUUAAAAGAAUCCAAAUUCAAACUAAA - example_title: hemoglobin subunit alpha 2 pipeline_tag: splice-site sequence_type: 3' UTR task: splice-site text: CUGGAGCCUCGGUAGCCGUUCCUCCUGCCCGCUGGGCCUCCCAACGGGCCCUCCUCCCCUCCUUGCACCGGCCCUUCCUGGUCUUUGAAUAAAGUCUGAGUGGGCAGCA - example_title: BRAF proto-oncogene pipeline_tag: splice-site sequence_type: 3' UTR task: splice-site text: AACAAAUGAGUGAGAGAGUUCAGGAGAGUAGCAACAAAAGGAAAAUAAAUGAACAUAUGUUUGCUUAUAUGUUAAAUUGAAUAAAAUACUCUCUUUUUUUUUAAGGUGAACCAAAGAACACUUGUGUGGUUAAAGACUAGAUAUAAUUUUUCCCCAAACUAAAAUUUAUACUUAACAUUGGAUUUUUAACAUCCAAGGGUUAAAAUACAUAGACAUUGCUAAAAAUUGGCAGAGCCUCUUCUAGAGGCUUUACUUUCUGUUCCGGGUUUGUAUCAUUCACUUGGUUAUUUUAAGUAGUAAACUUCAGUUUCUCAUGCAACUUUUGUUGCCAGCUAUCACAUGUCCACUAGGGACUCCAGAAGAAGACCCUACCUAUGCCUGUGUUUGCAGGUGAGAAGUUGGCAGUCGGUUAGCCUGGG - example_title: H3 clustered histone 1 pipeline_tag: splice-site sequence_type: 3' UTR task: splice-site text: UUACUGUGGUCUCUCUGACGGUCCAAGCAAAGGCUCUUUUCAGAGCCACCACCUUUUC --- # SpTransformer Transformer network for predicting tissue-specific splicing from pre-mRNA sequences. ## Disclaimer This is an UNOFFICIAL implementation of [SpliceTransformer predicts tissue-specific splicing linked to human diseases](https://doi.org/10.1038/s41467-024-53088-6) by Ningyuan You, et al. The OFFICIAL repository of SpliceTransformer (SpTransformer) is at [ShenLab-Genomics/SpliceTransformer](https://github.com/ShenLab-Genomics/SpliceTransformer). > [!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 SpTransformer did not write this model card for this model so this model card has been written by the MultiMolecule team.** ## Model Details SpTransformer (SpliceTransformer) is a deep neural network that predicts tissue-specific splicing from primary pre-mRNA sequence. It combines two pretrained SpliceAI-style dilated-residual convolutional feature extractors with a trainable input-projection path; the concatenated features are processed by a Sinkhorn transformer attention block with axial positional embeddings. For each position the network predicts a 3-channel splice-site score (no-splice / acceptor / donor) and a per-position splice-site usage score across 15 human tissues. The model uses a fixed flanking context of 4,000 nucleotides on each side of every predicted position. SpTransformer is typically used to estimate the effect of genetic variants on tissue-specific splicing by scoring reference and alternate sequences and taking the difference. Please refer to the [Training Details](#training-details) section for more information on the training process. ### Model Specification | Num Layers | Hidden Size | Num Heads | Intermediate Size | Max Seq Len | Num Parameters (M) | FLOPs (G) | MACs (G) | Context | | ---------- | ----------- | --------- | ----------------- | ----------- | ------------------ | --------- | -------- | ------- | | 8 | 256 | 8 | 1024 | 8192 | 17.07 | 290.72 | 144.65 | 4000 | ### Links - **Code**: [multimolecule.sptransformer](https://github.com/DLS5-Omics/multimolecule/tree/master/multimolecule/models/sptransformer) - **Data**: GTEx human RNA-seq across 15 tissues with gene annotations from GENCODE and multi-species sequence data - **Paper**: [SpliceTransformer predicts tissue-specific splicing linked to human diseases](https://doi.org/10.1038/s41467-024-53088-6) - **Developed by**: Ningyuan You, Chang Liu, Yuxin Gu, Rong Wang, Hanying Jia, Tianyun Zhang, Song Jiang, Jinsong Shi, Ming Chen, Min-Xin Guan, Siqi Sun, Shanshan Pei, Zhihong Liu, Ning Shen - **Model type**: Transformer encoder with windowed-local and Sinkhorn sorted-bucket attention for tissue-specific splicing prediction - **Original Repository**: [ShenLab-Genomics/SpliceTransformer](https://github.com/ShenLab-Genomics/SpliceTransformer) ## 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 #### RNA Splicing Site Prediction You can use this model directly to predict per-nucleotide tissue-specific splicing of a pre-mRNA sequence: ```python >>> from multimolecule import RnaTokenizer, SpTransformerModel >>> tokenizer = RnaTokenizer.from_pretrained("multimolecule/sptransformer") >>> model = SpTransformerModel.from_pretrained("multimolecule/sptransformer") >>> output = model(tokenizer("AGCAGUCAUUAUGGCGAA", return_tensors="pt")["input_ids"]) >>> output.keys() odict_keys(['last_hidden_state', 'logits']) ``` The `logits` tensor reproduces the original SpTransformer output: a 3-channel splice-site score (no-splice / acceptor / donor) and a per-tissue (15 tissues) splice-site usage score for each position. ### Downstream Use #### Token Prediction You can fine-tune SpTransformer for per-nucleotide tissue-specific splicing regression with [`SpTransformerForTokenPrediction`][multimolecule.models.SpTransformerForTokenPrediction], which adds a shared token prediction head on top of the backbone. ### Interface - **Input length**: variable pre-mRNA sequence - **Flanking context**: fixed 4,000 nt on each side of every predicted position - **Padding**: ends padded with `N` - **Output**: per-position 3-channel splice-site score (`no-splice` / `acceptor` / `donor`) + per-tissue (15 tissues) splice-site usage score ## Training Details SpTransformer was trained to predict tissue-specific splicing from primary pre-mRNA sequence. ### Training Data SpTransformer was trained on splicing measurements derived from RNA-seq data across 15 human tissues, using gene annotations from [GENCODE](https://multimolecule.danling.org/datasets/gencode), together with multi-species sequence data. The two convolutional feature extractors were pre-trained as SpliceAI-style splice-site predictors and remain trainable submodules for downstream fine-tuning. For each predicted nucleotide, a sequence window centered on that nucleotide was used, with the flanking context padded with `N` (unknown nucleotide) when near transcript ends. ### Training Procedure #### Pre-training The model was trained to minimize a combination of cross-entropy loss over splice-site classification and a regression loss over per-tissue splice-site usage, comparing predictions against measurements derived from RNA-seq. ## Citation ```bibtex @article{You2024, author = {You, Ningyuan and Liu, Chang and Gu, Yuxin and Wang, Rong and Jia, Hanying and Zhang, Tianyun and Jiang, Song and Shi, Jinsong and Chen, Ming and Guan, Min-Xin and Sun, Siqi and Pei, Shanshan and Liu, Zhihong and Shen, Ning}, title = {{SpliceTransformer predicts tissue-specific splicing linked to human diseases}}, journal = {Nature Communications}, year = {2024}, volume = {15}, number = {1}, pages = {9129}, month = {oct}, doi = {10.1038/s41467-024-53088-6}, issn = {2041-1723}, url = {https://doi.org/10.1038/s41467-024-53088-6} } ``` > [!NOTE] > The artifacts distributed in this repository are part of the MultiMolecule project. > If MultiMolecule supports your research, please 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 } ``` ## 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 [SpliceTransformer paper](https://doi.org/10.1038/s41467-024-53088-6) 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 ```