Yuning You
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README.md
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## Overview
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This is the PyTorch implementation of the CI-FM model -- an AI model that can simulate the activities within a living tissue (AI virtual tissue).
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The current version of CI-FM has 138M parameters and is trained on around 23M cells of spatial genomics. The signature functions of CI-FM are:
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- **Embedding** of celllular microenvironments via ```embeddings = model.embed(adata)``` (1st Figure below panel D top);
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- **Inference/simulation** of cellular gene expressions within a certain microenvironment via ```expressions = model.predict_cells_at_locations(adata, target_locs)``` (1st Figure below panel D bottom, and 2nd Figure below).
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The detailed usage of the model can be found in the [tutorial](https://huggingface.co/ynyou/CIFM/blob/main/test.ipynb).
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Before running the tutorial, please set up an environment following the [environment instruction](https://huggingface.co/ynyou/CIFM#environment).
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## Overview
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This is the PyTorch implementation of the CI-FM model -- an AI model that can simulate the activities within a living tissue (AI virtual tissue).
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17 |
The current version of CI-FM has 138M parameters and is trained on around 23M cells of spatial genomics. The signature functions of CI-FM are:
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- **Embedding** of celllular microenvironments via ```embeddings = model.embed(adata)``` (the 1st Figure below panel D top);
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- **Inference/simulation** of cellular gene expressions within a certain microenvironment via ```expressions = model.predict_cells_at_locations(adata, target_locs)``` (the 1st Figure below panel D bottom, and the 2nd Figure below).
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The detailed usage of the model can be found in the [tutorial](https://huggingface.co/ynyou/CIFM/blob/main/test.ipynb).
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Before running the tutorial, please set up an environment following the [environment instruction](https://huggingface.co/ynyou/CIFM#environment).
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