Published March 15, 2026 | Version v1
Model Open

The code and data for the work of Interpretability-guided simplification of breast cancer scRNA-seq model

  • 1. ROR icon Guizhou Education University

Description

This archive contains the code, processed datasets, pretrained weights, and example notebooks associated with our study on interpretability-guided simplification for breast cancer scRNA-seq prediction. It covers both cell-level and tumor-level analyses based on Smart-seq2 and MULTI-seq data, together with preprocessing scripts and reproducible usage examples. The files are packaged here as a single compressed resource for preservation, sharing, and citation.

Files

breast_cancer_sc_simplification_resource.zip

Files (13.7 GB)

Name Size Download all
md5:920a2499c33f839cee61921247752be7
13.7 GB Preview Download

Additional details

Funding

National Natural Science Foundation of China
22203057