Rakesh D. Barve

This study uses a literature-derived knowledge graph to improve scRNA-seq annotation by leveraging gene-cell type associations from biomedical texts.

The paper uses a data science platform to integrate biomedical text and single-cell RNA-seq data to identify new SARS-CoV-2 receptor expression patterns and potential infection targets.

The paper introduces a platform for real-time synthesis of biomedical knowledge using unsupervised neural networks, integrating unstructured literature with structured databases.