Ovidiu Radulescu

The paper investigates HIV-1 transcription variability using a dual-copy MS2-tagging system and mathematical analysis, finding that cellular heterogeneity influences the response to latency-reversing agents.

The paper introduces a method using Laplacian matrices and Kron reduction to simplify and analyze chemical reaction networks by modeling them as species-reaction graphs.

The paper introduces a new spatial entropy measure, RCE, to analyze categorical co-occurrences in spatial data across various fields, identifying environment-dependent interactions.

This paper introduces an algorithm for hierarchical decomposition of biochemical networks using causality and information flow, demonstrating computational efficiency and scalability through benchmarking.

The paper uses SMF and live imaging to study promoter dynamics, showing Tat influences nucleosome removal and polymerase activity.

The paper investigates how Snail-mediated repression coordinates cell fate decisions through transcription factor cooperativity and multiple inactive promoter states during development.

This study identifies G-quadruplexes as promoter elements that exclude nucleosomes and facilitate RNA polymerase II pausing.

The paper uses optogenetics to manipulate Dorsal levels in Drosophila embryos, revealing a critical temporal window for its function in patterning and transcriptional regulation.

The paper introduces HOSS, a hierarchical optimization framework for biochemical networks, which improves model efficiency and reusability by breaking down complex systems into modular, progressively optimized components.

The paper develops a data-driven mechanistic model to quantify hypoxia profiles in tumors using reaction-diffusion equations and vascular data.

This paper develops a computational model to predict outcomes of different therapeutic strategies in melanoma by analyzing single-cell mRNA sequencing data and simulating tumor heterogeneity and drug resistance.

This study shows that the transcription factor GAF acts as a stable mitotic bookmark during zygotic genome activation in Drosophila embryos, enabling rapid transcriptional activation after mitosis.

The paper uses single molecule imaging to study HIV-1 promoter pausing and finds that stochastic pausing leads to transcriptional bursting in latent cells.

The paper uses live imaging and computational methods to study how promoter motifs affect transcriptional bursting in Drosophila embryos, revealing distinct dynamics for TATA and INR motifs.

LNetReduce simplifies linear dynamic networks by reducing them while preserving dynamics across all time scales.

The paper introduces interval methods to analyze homeostasis and multistationarity in biochemical systems using existing models.

The paper analyzes gene regulation robustness in Drosophila using a sequence-level model, finding that enhancer length correlates with robustness to genetic perturbation.

The paper identifies metastable regimes in biochemical networks and links parameter sensitivity to cancer-specific alterations using tropical geometry and signaling network analysis.

The paper investigates how the pioneer factor Zelda controls gene expression timing through transient chromatin interactions in Drosophila embryos.

The paper develops piecewise-deterministic models to approximate gene network dynamics and evaluates methods for computing time-dependent stochastic distributions of mRNA and protein synthesis.