--- library_name: multimolecule license: agpl-3.0 pipeline: mean-ribosome-load pipeline_tag: other tags: - Biology - RNA - 5' UTR - Translation - rna widget: - example_title: microRNA 21 pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: UAGCUUAUCAGACUGAUGUUGA - example_title: microRNA 146a pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: UGAGAACUGAAUUCCAUGGGUU - example_title: microRNA 155 pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: UUAAUGCUAAUCGUGAUAGGGGUU - example_title: RNA component of mitochondrial RNA processing endoribonuclease pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: GGUUCGUGCUGAAGGCCUGUAUCCUAGGCUACACACUGAGGACUCUGUUCCUCCCCUUUCCGCCUAGGGGAAAGUCCCCGGACCUCGGGCAGAGAGUGCCACGUGCAUACGCACGUAGACAUUCCCCGCUUCCCACUCCAAAGUCCGCCAAGAAGCGUAUCCCGCUGAGCGGCGUGGCGCGGGGGCGUCAUCCGUCAGCUCCCUCUAGUUACGCAGGCAGUGCGUGUCCGCGCACCAACCACACGGGGCUCAUUCUCAGCGCGGCUGUAAAAAAAAA - example_title: 7SK small nuclear RNA pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: GGAUGUGAGGGCGAUCUGGCUGCGACAUCUGUCACCCCAUUGAUCGCCAGGGUUGAUUCGGCUGAUCUGGCUGGCUAGGCGGGUGUCCCCUUCCUCCCUCACCGCUCCAUGUGCGUCCCUCCCGAAGCUGCGCGCUCGGUCGAAGAGGACGACCAUCCCCGAUAGAGGAGGACCGGUCUUCGGUCAAGGGUAUACGAGUAGCUGCGCUCCCCUGCUAGAACCUCCAAACAAGCUCUCAAGGUCCAUUUGUAGGAGAACGUAGGGUAGUCAAGCUUCCAAGACUCCAGACACAUCCAAAUGAGGCGCUGCAUGUGGCAGUCUGCCUUUCUUUU - example_title: telomerase RNA component pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: GGGUUGCGGAGGGUGGGCCUGGGAGGGGUGGUGGCCAUUUUUUGUCUAACCCUAACUGAGAAGGGCGUAGGCGCCGUGCUUUUGCUCCCCGCGCGCUGUUUUUCUCGCUGACUUUCAGCGGGCGGAAAAGCCUCGGCCUGCCGCCUUCCACCGUUCAUUCUAGAGCAAACAAAAAAUGUCAGCUGCUGGCCCGUUCGCCCCUCCCGGGGACCUGCGGCGGGUCGCCUGCCCAGCCCCCGAACCCCGCCUGGAGGCCGCGGUCGGCCCGGGGCUUCUCCGGAGGCACCCACUGCCACCGCGAAGAGUUGGGCUCUGUCAGCCGCGGGUCUCUCGGGGGCGAGGGCGAGGUUCAGGCCUUUCAGGCCGCAGGAAGAGGAACGGAGCGAGUCCCCGCGCGCGGCGCGAUUCCCUGAGCUGUGGGACGUGCACCCAGGACUCGGCUCACACAUGC - example_title: vault RNA 2-1 pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: CGGGUCGGAGUUAGCUCAAGCGGUUACCUCCUCAUGCCGGACUUUCUAUCUGUCCAUCUCUGUGCUGGGGUUCGAGACCCGCGGGUGCUUACUGACCCUUUUAUGCAA - example_title: brain cytoplasmic RNA 1 pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: GGCCGGGCGCGGUGGCUCACGCCUGUAAUCCCAGCUCUCAGGGAGGCUAAGAGGCGGGAGGAUAGCUUGAGCCCAGGAGUUCGAGACCUGCCUGGGCAAUAUAGCGAGACCCCGUUCUCCAGAAAAAGGAAAAAAAAAAACAAAAGACAAAAAAAAAAUAAGCGUAACUUCCCUCAAAGCAACAACCCCCCCCCCCCUUU - example_title: HIV-1 TAR-WT pipeline_tag: mean-ribosome-load sequence_type: ncRNA task: mean-ribosome-load text: GGUCUCUCUGGUUAGACCAGAUCUGAGCCUGGGAGCUCUCUGGCUAACUAGGGAACC - example_title: prion protein (Kanno blood group) pipeline_tag: mean-ribosome-load sequence_type: mRNA task: mean-ribosome-load text: AUGGCGAACCUUGGCUGCUGGAUGCUGGUUCUCUUUGUGGCCACAUGGAGUGACCUGGGCCUCUGC - example_title: interleukin 10 pipeline_tag: mean-ribosome-load sequence_type: mRNA task: mean-ribosome-load text: AUGCACAGCUCAGCACUGCUCUGUUGCCUGGUCCUCCUGACUGGGGUGAGGGCC - example_title: Zaire ebolavirus pipeline_tag: mean-ribosome-load sequence_type: mRNA task: mean-ribosome-load text: AAUGUUCAAACACUUUGUGAAGCUCUGUUAGCUGAUGGUCUUGCUAAAGCAUUUCCUAGCAAUAUGAUGGUAGUCACAGAGCGUGAGCAAAAAGAAAGCUUAUUGCAUCAAGCAUCAUGGCACCACACAAGUGAUGAUUUUGGUGAGCAUGCCACAGUUAGAGGGAGUAGCUUUGUAACUGAUUUAGAGAAAUACAAUCUUGCAUUUAGAUAUGAGUUUACAGCACCUUUUAUAGAAUAUUGUAACCGUUGCUAUGGUGUUAAGAAUGUUUUUAAUUGGAUGCAUUAUACAAUCCCACAGUGUUAU - example_title: SARS coronavirus pipeline_tag: mean-ribosome-load sequence_type: mRNA task: mean-ribosome-load text: AUGUUUAUUUUCUUAUUAUUUCUUACUCUCACUAGUGGUAGUGACCUUGACCGGUGCACCACUUUUGAUGAUGUUCAAGCUCCUAAUUACACUCAACAUACUUCAUCUAUGAGGGGGGUUUACUAUCCUGAUGAAAUUUUUAGAUCAGACACUCUUUAUUUAACUCAGGAUUUAUUUCUUCCAUUUUAUUCUAAUGUUACAGGGUUUCAUACUAUUAAUCAUACGUUUGACAACCCUGUCAUACCUUUUAAGGAUGGUAUUUAUUUUGCUGCCACAGAGAAAUCAAAUGUUGUCCGUGGUUGGGUUUUUGGUUCUACCAUGAACAACAAGUCACAGUCGGUGAUUAUUAUUAACAAUUCUACUAAUGUUGUUAUACGAGCAUGUAACUUUGAAUUGUGUGACAACCCUUUCUUUGCUGUUUCUAAACCCAUGGGUACACAGACACAUACUAUGAUAUUCGAUAAUGCAUUUAAAUGCACUUUCGAGUACAUAUCU - example_title: insulin pipeline_tag: mean-ribosome-load sequence_type: mRNA task: mean-ribosome-load text: AUGGCCCUGUGGAUGCGCCUCCUGCCCCUGCUGGCGCUGCUGGCCCUCUGGGGACCUGACCCAGCCGCAGCCUUUGUGAACCAACACCUGUGCGGCUCACACCUGGUGGAAGCUCUCUACCUAGUGUGCGGGGAACGAGGCUUCUUCUACACACCCAAGACCCGCCGGGAGGCAGAGGACCUGCAGGUGGGGCAGGUGGAGCUGGGCGGGGGCCCUGGUGCAGGCAGCCUGCAGCCCUUGGCCCUGGAGGGGUCCCUGCAGAAGCGUGGCAUUGUGGAACAAUGCUGUACCAGCAUCUGCUCCCUCUACCAGCUGGAGAACUACUGCAACUAG - example_title: cyclin dependent kinase inhibitor 2A pipeline_tag: mean-ribosome-load sequence_type: mRNA task: mean-ribosome-load text: AUGGAGCCGGCGGCGGGGAGCAGCAUGGAGCCUUCGGCUGACUGGCUGGCCACGGCCGCGGCCCGGGGUCGGGUAGAGGAGGUGCGGGCGCUGCUGGAGGCGGGGGCGCUGCCCAACGCACCGAAUAGUUACGGUCGGAGGCCGAUCCAGGUCAUGAUGAUGGGCAGCGCCCGAGUGGCGGAGCUGCUGCUGCUCCACGGCGCGGAGCCCAACUGCGCCGACCCCGCCACUCUCACCCGACCCGUGCACGACGCUGCCCGGGAGGGCUUCCUGGACACGCUGGUGGUGCUGCACCGGGCCGGGGCGCGGCUGGACGUGCGCGAUGCCUGGGGCCGUCUGCCCGUGGACCUGGCUGAGGAGCUGGGCCAUCGCGAUGUCGCACGGUACCUGCGCGCGGCUGCGGGGGGCACCAGAGGCAGUAACCAUGCCCGCAUAGAUGCCGCGGAAGGUCCCUCAGACAUCCCCGAUUGA - example_title: human papillomavirus type 16 E6 pipeline_tag: mean-ribosome-load sequence_type: mRNA task: mean-ribosome-load text: AUGCACCAAAAGAGAACUGCAAUGUUUCAGGACCCACAGGAGCGACCCAGAAAGUUACCACAGUUAUGCACAGAGCUGCAAACAACUAUACAUGAUAUAAUAUUAGAAUGUGUGUACUGCAAGCAACAGUUACUGCGACGUGAGGUAUAUGACUUUGCUUUUCGGGAUUUAUGCAUAGUAUAUAGAGAUGGGAAUCCAUAUGCUGUAUGUGAUAAAUGUUUAAAGUUUUAUUCUAAAAUUAGUGAGUAUAGACAUUAUUGUUAUAGUUUGUAUGGAACAACAUUAGAACAGCAAUACAACAAACCGUUGUGUGAUUUGUUAAUUAGGUGUAUUAACUGUCAAAAGCCACUGUGUCCUGAAGAAAAGCAAAGACAUCUGGACAAAAAGCAAAGAUUCCAUAAUAUAAGGGGUCGGUGGACCGGUCGAUGUAUGUCUUGUUGCAGAUCAUCAAGAACACGUAGAGAAACCCAGCUGUAA - example_title: NRAS proto-oncogene pipeline_tag: mean-ribosome-load sequence_type: 5' UTR task: mean-ribosome-load text: GGGGCCGGAAGUGCCGCUCCUUGGUGGGGGCUGUUCAUGGCGGUUCCGGGGUCUCCAACAUUUUUCCCGGCUGUGGUCCUAAAUCUGUCCAAAGCAGAGGCAGUGGAGCUUGAGGUUCUUGCUGGUGUGAA - example_title: amyloid beta precursor protein pipeline_tag: mean-ribosome-load sequence_type: 5' UTR task: mean-ribosome-load text: GUCAGUUUCCUCGGCAGCGGUAGGCGAGAGCACGCGGAGGAGCGUGCGCGGGGGCCCCGGGAGACGGCGGCGGUGGCGGCGCGGGCAGAGCAAGGACGCGGCGGAUCCCACUCGCACAGCAGCGCACUCGGUGCCCCGCGCAGGGUCGCG - example_title: RUNX family transcription factor 1 pipeline_tag: mean-ribosome-load sequence_type: 5' UTR task: mean-ribosome-load text: ACUUCUUUGGGCCUCAUAAACAACCACAGAACCACAAGUUGGGUAGCCUGGCAGUGUCAGAAGUCUGAACCCAGCAUAGUGGUCAGCAGGCAGGACGAAUCACACUGAAUGCAAACCACAGGGUUUCGCAGCGUGGUAAAAGAAAUCAUUGAGUCCCCCGCCUUCAGAAGAGGGUGCAUUUUCAGGAGGAAGCG - example_title: fragile X messenger ribonucleoprotein 1 pipeline_tag: mean-ribosome-load sequence_type: 5' UTR task: mean-ribosome-load text: CUCAGUCAGGCGCUCAGCUCCGUUUCGGUUUCACUUCCGGUGGAGGGCCGCCUCUGAGCGGGCGGCGGGCCGACGGCGAGCGCGGGCGGCGGCGGUGACGGAGGCGCCGCUGCCAGGGGGCGUGCGGCAGCGCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGAGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCUGGGCCUCGAGCGCCCGCAGCCCACCUCUCGGGGGCGGGCUCCCGGCGCUAGCAGGGCUGAAGAGAAG - example_title: MYC proto-oncogene pipeline_tag: mean-ribosome-load sequence_type: 5' UTR task: mean-ribosome-load text: AACUCGCUGUAGUAAUUCCAGCGAGAGGCAGAGGGAGCGAGCGGGCGGCCGGCUAGGGUGGAAGAGCCGGGCGAGCAGAGCUGCGCUGCGGGCGUCCUGGGAAGGGAGAUCCGGAGCGAAUAGGGGGCUUCGCCUCUGGCCCAGCCCUCCCGCUGAUCCCCCAGCCAGCGGUCCGCAACCCUUGCCGCAUCCACGAAACUUUGCCCAUAGCAGCGGGCGGGCACUUUGCACUGGAACUUACAACACCCGAGCAAGGACGCGACUCUCCCGACGCGGGGAGGCUAUUCUGCCCAUUUGGGGACACUUCCCCGCCGCUGCCAGGACCCGCUUCUCUGAAAGGCUCUCCUUGCAGCUGCUUAGACG - example_title: activating transcription factor 4 pipeline_tag: mean-ribosome-load sequence_type: 5' UTR task: mean-ribosome-load text: CAUUUCUACUUUGCCCGCCCACAGAUGUAGUUUUCUCUGCGCGUGUGCGUUUUCCCUCCUCCCCGCCCUCAGGGUCCACGGCCACCAUGGCGUAUUAGGGGCAGCAGUGCCUGCGGCAGCAUUGGCCUUUGCAGCGGCGGCAGCAGCACCAGGCUCUGCAGCGGCAACCCCCAGCGGCUUAAGCCAUGGCGCUUCUCACGGCAUUCAGCAGCAGCGUUGCUGUAACCGACAAAGACACCUUCGAAUUAAGCACAUUCCUCGAUUCCAGCAAAGCACCGCAAC - example_title: Human GPI protein p137 pipeline_tag: mean-ribosome-load sequence_type: 3' UTR task: mean-ribosome-load text: UUUUUAAAAGGAAAAGAUACCAAAUGCCUGCUGCUACCACCCUUUUCAAUUGCUAUGUUUUGAAAGGCACCAGUAUGUGUUUUAGAUUGAUUUAAAUGUUUCAUUUAAAUCACGGACAGUAGUUUCAGUUCUGAUGGUAUAAGCAAAACAAAUAAAACGUUUAUAAAAGUUGUAUCUUGAAACACUGGUGUUCAACAGCUAGCAGCUUAUGUGAUUCACCCCAUGCCACGUUAGUGUCACAAAUUUUAUGGUUUAUCUCCAGCAACAUUUCUCUAGUACUUGCACUUAUUAUCUGAAUUC - example_title: nucleophosmin 1 pipeline_tag: mean-ribosome-load sequence_type: 3' UTR task: mean-ribosome-load text: GAAAAUAGUUUAAACAAUUUGUUAAAAAAUUUUCCGUCUUAUUUCAUUUCUGUAACAGUUGAUAUCUGGCUGUCCUUUUUAUAAUGCAGAGUGAGAACUUUCCCUACCGUGUUUGAUAAAUGUUGUCCAGGUUCUAUUGCCAAGAAUGUGUUGUCCAAAAUGCCUGUUUAGUUUUUAAAGAUGGAACUCCACCCUUUGCUUGGUUUUAAGUAUGUAUGGAAUGUUAUGAUAGGACAUAGUAGUAGCGGUGGUCAGACAUGGAAAUGGUGGGGAGACAAAAAUAUACAUGUGAAAUAAAACUCAGUAUUUUAAUAAAGUAGCACGGUUUCUAUUGA - example_title: superoxide dismutase 1 pipeline_tag: mean-ribosome-load sequence_type: 3' UTR task: mean-ribosome-load text: ACAUUCCCUUGGAUGUAGUCUGAGGCCCCUUAACUCAUCUGUUAUCCUGCUAGCUGUAGAAAUGUAUCCUGAUAAACAUUAAACACUGUAAUCUUAAAAGUGUAAUUGUGUGACUUUUUCAGAGUUGCUUUAAAGUACCUGUAGUGAGAAACUGAUUUAUGAUCACUUGGAAGAUUUGUAUAGUUUUAUAAAACUCAGUUAAAAUGUCUGUUUCAAUGACCUGUAUUUUGCCAGACUUAAAUCACAGAUGGGUAUUAAACUUGUCAGAAUUUCUUUGUCAUUCAAGCCUGUGAAUAAAAACCCUGUAUGGCACUUAUUAUGAGGCUAUUAAAAGAAUCCAAAUUCAAACUAAA - example_title: hemoglobin subunit alpha 2 pipeline_tag: mean-ribosome-load sequence_type: 3' UTR task: mean-ribosome-load text: CUGGAGCCUCGGUAGCCGUUCCUCCUGCCCGCUGGGCCUCCCAACGGGCCCUCCUCCCCUCCUUGCACCGGCCCUUCCUGGUCUUUGAAUAAAGUCUGAGUGGGCAGCA - example_title: BRAF proto-oncogene pipeline_tag: mean-ribosome-load sequence_type: 3' UTR task: mean-ribosome-load text: AACAAAUGAGUGAGAGAGUUCAGGAGAGUAGCAACAAAAGGAAAAUAAAUGAACAUAUGUUUGCUUAUAUGUUAAAUUGAAUAAAAUACUCUCUUUUUUUUUAAGGUGAACCAAAGAACACUUGUGUGGUUAAAGACUAGAUAUAAUUUUUCCCCAAACUAAAAUUUAUACUUAACAUUGGAUUUUUAACAUCCAAGGGUUAAAAUACAUAGACAUUGCUAAAAAUUGGCAGAGCCUCUUCUAGAGGCUUUACUUUCUGUUCCGGGUUUGUAUCAUUCACUUGGUUAUUUUAAGUAGUAAACUUCAGUUUCUCAUGCAACUUUUGUUGCCAGCUAUCACAUGUCCACUAGGGACUCCAGAAGAAGACCCUACCUAUGCCUGUGUUUGCAGGUGAGAAGUUGGCAGUCGGUUAGCCUGGG - example_title: H3 clustered histone 1 pipeline_tag: mean-ribosome-load sequence_type: 3' UTR task: mean-ribosome-load text: UUACUGUGGUCUCUCUGACGGUCCAAGCAAAGGCUCUUUUCAGAGCCACCACCUUUUC --- # OptMRL Convolutional neural network for predicting the mean ribosome load (MRL) of an mRNA from the 50 nucleotides upstream of the coding sequence. ## Disclaimer This is an UNOFFICIAL implementation of [Interpreting Deep Neural Networks for the Prediction of Translation Rates](https://doi.org/10.1101/2023.06.02.543405) by Frederick Korbel, et al. The OFFICIAL repository of OptMRL is at [ohlerlab/mlcis](https://github.com/ohlerlab/mlcis). > [!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 OptMRL did not write this model card for this model so this model card has been written by the MultiMolecule team.** ## Model Details OptMRL is a small 1D convolutional neural network trained to predict the mean ribosome load (MRL), a polysome-profiling-derived translation efficiency proxy, from the 50 nucleotides of 5' untranslated region (5'UTR) sequence immediately upstream of the coding sequence. The model was first pre-trained on roughly 260,000 random 5'UTR reporters and then fine-tuned on roughly 20,000 endogenous human 5'UTRs. Please refer to the [Training Details](#training-details) section for more information on the training process. The architecture is a stack of three `Conv1D` layers (120 filters, kernel size 8, `same` padding, ReLU activation) followed by a `Flatten`, a 40-unit `Dense` bottleneck with ReLU activation and dropout, and a final scalar `Dense` regression head. ### Model Specification | Num Layers | Hidden Size | Num Parameters (M) | FLOPs (M) | MACs (M) | Max Num Tokens | | ---------- | ----------- | ------------------ | --------- | -------- | -------------- | | 5 | 40 | 0.476 | 24.04 | 12.00 | 50 | ### Links - **Code**: [multimolecule.optmrl](https://github.com/DLS5-Omics/multimolecule/tree/master/multimolecule/models/optmrl) - **Data**: 260,000 random 5'UTR reporters (pre-training) + 20,000 human 5'UTR reporters (fine-tuning) - **Paper**: [Interpreting Deep Neural Networks for the Prediction of Translation Rates](https://doi.org/10.1101/2023.06.02.543405) - **Developed by**: Frederick Korbel, Ekaterina Eroshok, Uwe Ohler - **Model type**: 1D CNN for mean-ribosome-load regression from 5'UTR sequence - **Original Repository**: [ohlerlab/mlcis](https://github.com/ohlerlab/mlcis) ## 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 #### Mean Ribosome Load Prediction You can use this model directly to predict the mean ribosome load of a 50-nucleotide 5'UTR window: ```python >>> from multimolecule import RnaTokenizer, OptMrlForSequencePrediction >>> tokenizer = RnaTokenizer.from_pretrained("multimolecule/optmrl") >>> model = OptMrlForSequencePrediction.from_pretrained("multimolecule/optmrl") >>> sequence = "ACGU" * 12 + "AC" # 50 nt >>> input = tokenizer(sequence, add_special_tokens=False, return_tensors="pt") >>> output = model(**input) >>> output.logits.shape torch.Size([1, 1]) ``` ### Interface - **Input length**: 50 nt fixed 5'UTR window taken immediately upstream of the coding sequence - **Padding**: shorter sequences are right-padded with zeros to 50 nt; longer sequences are truncated to the first 50 nt - **Alphabet**: `ACGU` only; unknown / `N` tokens contribute zero one-hot signal - **Special tokens**: do not add (`add_special_tokens=False`) - **Output**: single scalar mean-ribosome-load (MRL) score per window ## Training Details OptMRL was first pre-trained on a large random-5'UTR reporter library and then fine-tuned on a smaller library of endogenous human 5'UTRs. ### Training Data - **Pre-training**: ~260,000 random 5'UTR reporters paired with polysome-profiling MRL measurements. - **Fine-tuning**: ~20,000 endogenous human 5'UTR reporters paired with polysome-profiling MRL measurements. Each reporter contributes a 50-nucleotide 5'UTR window immediately upstream of the coding sequence and a scalar MRL label. Note [`RnaTokenizer`][multimolecule.RnaTokenizer] will convert "T"s to "U"s for you, you may disable this behaviour by passing `replace_T_with_U=False`. ### Training Procedure #### Pre-training The model was first pre-trained as a regression task to predict the measured MRL of each random 5'UTR reporter, then fine-tuned end-to-end on the human-5'UTR reporters using the same regression objective. The published model is the fine-tuned model. ## Citation ```bibtex @article{korbel2023interpreting, author = {Korbel, Frederick and Eroshok, Ekaterina and Ohler, Uwe}, title = {Interpreting Deep Neural Networks for the Prediction of Translation Rates}, journal = {bioRxiv}, publisher = {Cold Spring Harbor Laboratory}, year = {2023}, doi = {10.1101/2023.06.02.543405} } ``` > [!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 [OptMRL paper](https://doi.org/10.1101/2023.06.02.543405) 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 ```