Turki Turki

This study uses tensor decomposition to analyze gene expression data and finds non-linear dose dependence can occur with single drugs, not just drug combinations.

This paper develops and evaluates deep learning models to detect metastatic breast cancer in axillary lymph nodes using digital pathology images, finding DenseNet121 achieves the highest performance.

This paper introduces a tensor-decomposition-based unsupervised feature extraction method for multiomics data, showing it outperforms existing methods in selecting biologically relevant genes.

The paper applies tensor decomposition-based unsupervised feature extraction to gene expression data from drug-treated mouse tissues, identifying common drug effects across tissue groups.

The paper screens genes differentially expressed in Alzheimer's disease model mice and finds overlap with drug-treated human cell lines using tensor decomposition.

This paper applies tensor decomposition-based unsupervised feature extraction to integrate human and mouse scRNA-seq data, improving gene selection and identifying potential regulatory transcription factors.