The development, interpretation, and validation of AI models as key considerations for their integration and analysis are discussed, and practical suggestions for improving the reliability and biological relevance of AI-driven discoveries are provided.
Yu-Han Sun, Olivia J. Cheng, A. Ma et al.· Genome Biology· 0 citations
EmitGCL is developed, a deep-learning framework to predict metastasis and related biomarkers using cancer single-cell sequencing data, enabling and validating the discovery of occult metastases and breast cancer metastasis biomarkers.
Xiaoying Wang, Maoteng Duan, Anthony J. Snyder et al.· Nature Communications· 0 citations
EmitGCL, a deep-learning framework that accurately predicts future metastasis and its corresponding biomarkers, is presented and YY1 transcription factor is demonstrated as a key driver of breast cancer metastasis which was validated through in-silico and CRISPR-based migration assays, suggesting that YY1 is a potentia...
Xiaoying Wang, Maoteng Duan, Po-Lan Su et al.· bioRxiv· 0 citations
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