Vahid Shahrezaei

Bayesian model discovery for reverse-engineering biochemical networks from data

This paper introduces a Bayesian sparse likelihood-free inference method to reverse-engineer biochemical networks from single-cell data, showing high accuracy and outperforming correlation-based methods.

Overinflation and overconcentration: why Cauchy perturbation kernels are the right choice for ABC-SMC

This paper shows that Cauchy perturbation kernels outperform Normal kernels in ABC-SMC by addressing overinflation and overconcentration issues, improving performance in high dimensions.

An integrated stress response-independent role of GCN2 prevents excessive ribosome biogenesis and mRNA translation

This study identifies an ISR-independent role of GCN2 in preventing excessive ribosome biogenesis and mRNA translation, with implications for cancer therapy.

Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA-sequencing

This study uses a stochastic model to analyze time-resolved single-cell RNA-sequencing data and identifies global transcription regulation mechanisms through dynamical correlations.

Forecasting the adoption and spread of a community-based marine management initiative using agent-based models

This paper uses agent-based models and Bayesian inference to forecast the adoption and spread of a marine management initiative in Fiji, identifying key drivers and informing conservation policy.

Inference of the core gene regulatory network underlying seam cell development in Caenorhabditis elegans

The paper infers the core gene regulatory network governing seam cell development in C. elegans using smFISH data and computational models.

Multi-signal regulation of the GSK-3β homolog Rim11 governs meiosis entry in yeast

The paper shows how Rim11 integrates signals from PKA, TORC1, and Ime1 to regulate Ume6 phosphorylation and drive meiotic gene expression in yeast.

A coarse-grained resource allocation model of carbon and nitrogen metabolism in unicellular microbes

This paper develops a coarse-grained resource allocation model to explain cellular growth laws and resource allocation strategies in unicellular microbes.

Modelling capture efficiency of single cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics

The paper develops a method to model capture efficiency in scRNA-seq data to improve inference of transcriptome-wide burst kinetics.

Fission yeast obeys a linear size law under nutrient titration

This paper investigates how cell size and geometry in fission yeast vary under different growth conditions and finds that cell volume and growth rate follow a linear scaling under nitrogen and carbon titration.

Efficient inference for agent-based models of real-world phenomena

This paper compares machine learning methods to improve inference efficiency for agent-based simulations of real-world phenomena like tumor growth and disease spread.

Benchmarking imputation methods for network inference using a novel method of synthetic scRNA-seq data generation

The paper benchmarks imputation methods for gene regulatory network inference using synthetic scRNA-seq data generated by a novel tool.

Growth-Rate Dependent And Nutrient-Specific Gene Expression Resource Allocation In Fission Yeast

This study investigates how growth rate and nutrient-specific factors influence gene expression in fission yeast, revealing coordinated and condition-specific regulation of metabolic enzymes.

Coordination of gene expression noise with cell size: analytical results for agent-based models of growing cell populations

The paper develops an agent-based framework to model gene expression noise in growing cell populations and shows it aligns with the chemical master equation under stochastic concentration homeostasis.

A push-pull system of repressors matches levels of glucose transporters to extracellular glucose in budding yeast

The paper shows that budding yeast use a push-pull repression system to dynamically match glucose transporter levels to extracellular glucose concentrations.

Ohm's Law for increasing fitness gene expression with selection pressure

The paper shows antibiotic resistance genes in E. coli exhibit dose-responsive expression under increasing antibiotic concentration, analogous to Ohm's law, and identifies mechanisms involving mRNA/protein variation and cell memory.

Size-dependent increase in RNA Polymerase II initiation rates mediates gene expression scaling with cell size

The paper investigates how RNA Polymerase II initiation rates scale with cell size in fission yeast, showing that RNAPII is a limiting factor for transcriptional scaling.

Epimutations driven by small RNAs arise frequently but have limited duration in a metazoan organism

This study investigates epimutations driven by small RNAs in C. elegans, finding they arise frequently but have limited duration.

Integrating multi-OMICS data through sparse Canonical Correlation Analysis for predicting complex traits: A comparative study

This paper compares methods for integrating multi-OMICS data using sparse canonical correlation analysis to improve prediction of complex traits.

bayNorm: Bayesian gene expression recovery, imputation and normalisation for single cell RNA-sequencing data

bayNorm provides a Bayesian method for normalizing, imputing, and recovering gene expression in scRNA-seq data, improving accuracy and reducing batch effects.

Single-cell phenotyping and RNA sequencing reveal novel patterns of gene expression heterogeneity and regulation during growth and stress adaptation in a unicellular eukaryote

The paper uses scRNA-seq and imaging to study gene expression heterogeneity in fission yeast under different environmental conditions, revealing how gene expression varies during growth and stress responses.

Division rate, cell size and proteome allocation: impact on gene expression noise and implications for the dynamics of genetic circuits

The paper models stochastic gene expression in growing cells to show how division rates affect noise in mRNA and protein levels, and how cell size regulation impacts circuit robustness.