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@@ -43,6 +43,17 @@ output = model(adata)
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  * https://github.com/apliko-xyz/PyTDC/blob/main/tdc/model_server/models/scvi.py
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  * weights extracted from https://cellxgene.cziscience.com/census-models
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  ## References
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  * Lopez, R., Regier, J., Cole, M., Jordan, M. I., & Yosef, N. (2018). Deep Generative Modeling for Single-cell Transcriptomics. Nature Methods, 15, 1053-1058.
 
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  * https://github.com/apliko-xyz/PyTDC/blob/main/tdc/model_server/models/scvi.py
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  * weights extracted from https://cellxgene.cziscience.com/census-models
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+ # TDC Citation
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+ ```
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+ @inproceedings{
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+ velez-arce2024signals,
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+ title={Signals in the Cells: Multimodal and Contextualized Machine Learning Foundations for Therapeutics},
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+ author={Alejandro Velez-Arce and Xiang Lin and Kexin Huang and Michelle M Li and Wenhao Gao and Bradley Pentelute and Tianfan Fu and Manolis Kellis and Marinka Zitnik},
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+ booktitle={NeurIPS 2024 Workshop on AI for New Drug Modalities},
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+ year={2024},
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+ url={https://openreview.net/forum?id=kL8dlYp6IM}
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+ }
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+ ```
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  ## References
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  * Lopez, R., Regier, J., Cole, M., Jordan, M. I., & Yosef, N. (2018). Deep Generative Modeling for Single-cell Transcriptomics. Nature Methods, 15, 1053-1058.