2 papers
quant-ph2026
Quantum Hamiltonian-Based Generative Modeling of Single-Cell Transcriptomics for Gene Regulatory Network Inference
Mohammad Aamir Sohail, Ranga R. Sudharshan, S. Sandeep Pradhan +1
We introduce a novel quantum Hamiltonian-based gene expression model (QHGM), a generative framework for modeling pseudotime-ordered single-cell gene expression data. In QHGM, gene…
stat.AP2025
Efficient inference of dynamic gene regulatory networks using discrete penalty
Visweswaran Ravikumar, Aaresh Bhathena, Wajd N Al-Holou +2
Gene regulatory networks (GRNs) orchestrate cellular decision making and survival strategies. Inferring the structure of these networks from high-dimensional transcriptomics data i…