Polina Bombina

This paper evaluates how dimensionality reduction methods affect trajectory geometry by testing their path-preservation across different point-density thresholds on linear and cyclic single-cell datasets.

This study identifies Treg destabilization as a staged differentiation process in atherosclerosis, leading to diverse exTreg states driven by IL-6R signaling.

The paper shows that pooled correlations in transcriptomic data often reverse sign when analyzed within specific contexts, highlighting the need for context-aware reporting of correlations.

scDIG is an R Shiny tool for interactive density-based gating of single-cell proteomic and transcriptomic data, resolving CD4+ T cell subpopulations in CITE-seq data.

The paper develops a method called Newmanization to reduce tissue signals in transcriptomic data and applies it to digestive tract cancer samples, showing improved clustering and separation compared to mutation data.

WayFindR converts pathway data into graph structures to analyze feedback loops, revealing their underrepresentation in curated databases.

This study evaluates 16 dimensionality reduction methods for CyTOF, scRNA-seq, and CITE-seq data, focusing on their ability to preserve pairwise distances and local neighborhoods.

SillyPutty improves clustering by optimizing silhouette width, showing comparable accuracy to existing methods and better performance when combined with hierarchical clustering.