Asish Kumar Swain

Deep learning-based method to identify disease-resistance proteins in Oryza sativa and relative species

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: spatially aware scalable and accurate tool for spot deconvolution and clustering in spatial transcriptomics

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.

Single-Cell Transcriptome Analysis Identifies Novel Biomarkers Involved in Major Liver Cancer Subtypes

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

Comparison of Dimensionality Reduction and Clustering Methods for Single-Cell Transcriptomics Data

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