Vinod Kumar Gupta

The paper introduces a disease-agnostic Nasal Microbiome Wellness Index (NMWI) that quantitatively assesses nasal microbiome health using 16S rRNA gene data, outperforming traditional diversity indices in distinguishing healthy from non-healthy samples.

The paper introduces GMWI2, a gut microbiome health index that improves disease prediction accuracy compared to previous models and traditional diversity indices.

TaxiBGC improves BGC prediction in metagenomes by using taxonomy-guided methods, showing better performance than read-based approaches and linking BGCs to human diseases.

The paper introduces GMHI-webtool, an online tool that computes and visualizes gut microbiome health indices from stool metagenomic data, enabling easier interpretation and comparison with reference datasets.

The paper introduces a gut microbiome health index (GMHI) that predicts general health status using species-level profiling and validates its robustness across multiple datasets.

The paper uses mass cytometry to analyze immune cell subsets in PBC patients and controls, identifying differences in cell abundance associated with disease and disease stage.