Fig. 1
From: scSMD: a deep learning method for accurate clustering of single cells based on auto-encoder
Workflow of scSMD. A Encoder-Decoder Framework: A denoising convolutional autoencoder based on a Negative Binomial (NB) model is trained to obtain a latent space representation and perform preliminary clustering in the latent space. The encoder integrates a novel Multi-dilated Attention Gate to enhance feature selection and representation. B Cellnet Construction: Utilizes pairwise data similarity metrics to construct Cellnet, enabling the model to more effectively capture structural relationships within the data. C Algorithm Specifications and Implementation: Provides comprehensive details on the algorithm’s specifications, emphasizing the Multi-dilated Attention Gate component. This component improves interpretability and contributes to the enhanced performance of scSMD