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README.md

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 # Overview
-The AIDO.Tissue model is develpoed on spatial single-cell transcriptomic data. To incorporate spatial cell information, K nearest neighbor cells (K=8 in our case) are retrieved for each center cell. The center cell and neighbor cell expression vectors are concatenated as model input. Two-dimension positional rotary embedding are introduced to encode both the gene and cell information. The first dim is gene index and second dim is cell index. The overall training scheme is similar to scFoundation with an asymmetric encoder-decoder architecture. 
+The AIDO.Tissue model is developed on spatial single-cell transcriptomic data. To incorporate spatial cell information, K nearest neighbor cells (K=8 in our case) are retrieved for each center cell. The center cell and neighbor cell expression vectors are concatenated as model input. Two-dimension positional rotary embedding are introduced to encode both the gene and cell information. The first dim is gene index and second dim is cell index. The overall training scheme is similar to scFoundation with an asymmetric encoder-decoder architecture. 
 
 # Results