N Bhattacharya

SecDATA: Secure Data Access and de novo TranscriptAssembly protocol - To meet the challenge of reliableNGS data analysis

SecDATA provides a secure data access protocol with a graph-based de novo transcript assembly method, outperforming existing tools in transcript reconstruction.

InGene: Finding influential genes from embeddings of nonlinear dimension reduction techniques

InGene identifies influential genes in scRNA-seq data by assigning importance scores based on their contribution to nonlinear dimensionality reduction maps.

scSPARKL: Apache Spark based parallel analytical framework for the downstream analysis of scRNA-seq data.

scSPARKL is a parallel analytical framework for scRNA-seq data that uses Apache Spark to handle large datasets through data reshaping, preprocessing, filtering, normalization, dimensionality reduction, and clustering.

Marker-free characterization of single live circulating tumor cell full-length transcriptomes

The paper introduces unCTC, an R package for unbiased identification and characterization of CTCs from scRNA-Seq data, validated on breast CTCs.

SCellBOW: AI-Driven Tumor Risk Stratification from Single-Cell Transcriptomics Using Phenotype Algebra

SCellBOW identifies and risk-stratifies tumor cell subpopulations using scRNA-seq data by simulating their impact on disease prognosis.

Simultaneous visualization of cells and marker genes from scRNA-seq studies

Stardust is a visualization method that embeds cells and marker genes together on a 2D map, performing competitively with existing tools on scRNA-seq and spatial transcriptomics data.