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README.md
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# jglaser/protein-ligand-mlp-1
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps
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<!--- Describe your model here -->
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Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
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```
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pip install -U sentence-transformers
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```
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Then you can use the model like this:
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```python
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from sentence_transformers import SentenceTransformer
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sentences = [
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model = SentenceTransformer('jglaser/protein-ligand-mlp-1')
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embeddings = model.encode(sentences)
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```
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## Evaluation Results
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<!--- Describe how your model was evaluated -->
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For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=jglaser/protein-ligand-mlp-1)
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## Full Model Architecture
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```
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SentenceTransformer(
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```
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## Citing & Authors
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# jglaser/protein-ligand-mlp-1
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps pairs of protein and chemical sequences (canonical SMILES) onto binding affinities (pIC50 values).
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Each member of the ensemble has been trained using a different seed and you can use the different models as independent samples to estimate the uncertainty.
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<!--- Describe your model here -->
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Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
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```
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#pip install -U sentence-transformers
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pip install git+https://github.com/jglaser/sentence-transformers.git@enable_mixed
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```
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Then you can use the model like this:
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```python
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from sentence_transformers import SentenceTransformer
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sentences = [{'protein': ["SEQVENCE"], 'ligand': ["c1ccccc1"]}]
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model = SentenceTransformer('jglaser/protein-ligand-mlp-1')
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embeddings = model.encode(sentences)
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```
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## Evaluation Results
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<!--- Describe how your model was evaluated -->
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## Full Model Architecture
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```
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SentenceTransformer(
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```
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## Citing & Authors
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- [Andrew E Blanchard](https://github.com/blnchrd)
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- [John Gounley](https://github.com/gounley)
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- [Debsindhu Bhowmik](https://github.com/debsindhu)
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- [Mayanka Chandra Shekar](https://github.com/mayankachandrashekar)
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- [Isaac Lyngaas](https://github.com/irlyngaas)
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- Shang Gao
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- Junqi Yin
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- Aristeidis Tsaris
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- Feiyi Wang
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- [Jens Glaser](https://github.com/jglaser)
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Find more information in our [bioRxiv preprint](https://www.biorxiv.org/content/10.1101/2021.12.10.471928v1)
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