1 citations · 1 across the 4 of their papers we have counts for
4 papers
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-…
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…
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…
Quantum gene regulatory networks
Cristhian Roman-Vicharra, James J. Cai
In this work, we present a quantum circuit model for inferring gene regulatory networks (GRNs). The model is based on the idea of using qubit-qubit entanglement to simulate interac…