3 papers
q-bio.QM2026
Quantum Generative Modeling of Single-Cell transcriptomes: Capturing Gene-Gene and Cell-Cell Interactions
Selim Romero, Vignesh S. Kumar, Robert S. Chapkin +1
Single-cell RNA sequencing (scRNA-seq) data simulation is limited by classical methods relying on linear correlations, failing to capture nonlinear dependencies. No existing simula…
cs.ET2026
QuantumXCT: Learning Interaction-Induced State Transformation in Cell-Cell Communication via Quantum Entanglement and Generative Modeling
Selim Romero, Shreyan Gupta, Robert S. Chapkin +1
Inferring cell-cell communication (CCC) from single-cell transcriptomics remains fundamentally limited by reliance on curated ligand-receptor databases, which primarily capture co-…
q-bio.GN2025
Quantum Annealing for Enhanced Feature Selection in Single-Cell RNA Sequencing Data Analysis
Selim Romero, Shreyan Gupta, Victoria Gatlin +2
Feature selection is a machine learning technique for identifying relevant variables in classification and regression models. In single-cell RNA sequencing (scRNA-seq) data analysi…