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Browse files- .gitattributes +2 -0
- README.md +36 -3
- ccd.pkl +3 -0
- intfold_v0.1.0.pt +3 -0
- nucleic_acid_id_groups.json +0 -0
- protein_id_groups.json +3 -0
- unique_nucleic_acid_sequences.fasta +0 -0
- unique_protein_sequences.fasta +3 -0
.gitattributes
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README.md
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---
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license: apache-2.0
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---
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license: apache-2.0
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tags:
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- biology
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- chemistry
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- IntFold
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- biomolecular-structure-prediction
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---
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<!--  -->
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# IntFold
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[](https://huggingface.co/GAGABIG/CNN)
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[](https://pypi.org/project/intfold/)
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[](LICENSE)
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[](#contact-us)
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<div align="center" style="margin: 20px 0;">
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<span style="margin: 0 10px;">⚡ <a href="https://server.intfold.com">IntFold Server</a></span>
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• <span style="margin: 0 10px;">📄 <a href="xxxxx">Technical Report</a></span>
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</div>
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**IntFold:** An open-source PyTorch implementation of [AlphaFold 3](https://www.nature.com/articles/s41586-024-07487-w). Predict biomolecular structures with state-of-the-art accuracy in a flexible framework.
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## 🚀 Quick Start
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To quickly get started with IntFold, you can use the following commands:
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```bash
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# Install IntFold from PyPI
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pip install intfold
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# Run inference with an example YAML file
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intfold predict ./examples/5S8I_A.yaml --out_dir ./output
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```
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ccd.pkl
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intfold_v0.1.0.pt
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nucleic_acid_id_groups.json
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protein_id_groups.json
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unique_nucleic_acid_sequences.fasta
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unique_protein_sequences.fasta
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