Asish Kumar Swain

This study develops a deep learning model to identify disease-resistance proteins in rice and related species, showing superior performance compared to traditional machine learning methods.

SpatialPrompt improves spot deconvolution and domain identification in spatial transcriptomics by integrating spatial coordinates and scRNA-seq data, showing scalability and accuracy across multiple datasets.

The paper uses scRNA-seq data to identify molecular markers and cell types associated with liver cancer subtypes HCC and ICC.

The paper benchmarks DR and clustering methods on scRNA-seq datasets, finding dataset-dependent performance and no single best method.