Tamir Tuller

The paper develops an optimized SSU-seq protocol for E. coli to study ribosome-mRNA interactions, revealing patterns of small subunit distribution linked to rRNA-mRNA hybridization.

The paper develops an embryo-safe NDV vaccine by using structure-aware synonymous mutations to modulate RNA folding, achieving high hatchability and protection against NDV challenge.

The paper identifies context-dependent factors affecting CRISPR-Cas9 editing efficiency across species using endogenous editing data and shows that repair outcomes are conserved.

This study shows that high dimensional silent patterns in viral coding regions encode regulatory codes related to viral tropism using a novel computational measure.

This study develops a bacterial biosensor for DNT detection using computational models to guide design, achieving improved sensitivity and specificity.

The paper introduces a gene fusion strategy using machine learning to improve the evolutionary stability of synthetic gene circuits in yeast.

The paper identifies mutation blocks in GCB lymphoma patients that affect transcription factor binding and gene expression, linking them to cancer development.

The paper develops Triggate, a computational tool for designing toehold switches with improved on/off ratios in both prokaryotes and eukaryotes.

The paper trains AI models to predict codon sequences from amino acid sequences in yeast and bacteria, showing they outperform frequency-based methods and reveal codon usage patterns linked to evolutionary pressures.

EXPosition is a computational tool for CRISPR gRNA design that optimizes gene expression effects using deep learning models for transcription, splicing, and translation initiation.

This paper introduces Oncosplice, a tool that identifies deleterious cancer mutations by analyzing mRNA splicing, finding 8K significant variants with 94% positive predictive value.

This study uses computational methods to analyze the effects of MDR1 variants on gene expression and patient prognosis, finding that T1236C increases MDR1 levels and correlates with worse prognosis.

The paper develops a mathematical model to study competition for shared translation resources among mRNAs and shows that adding mRNAs reduces pool density and total protein production.

The paper shows rRNA-mRNA interactions influence all translation steps in bacteria and shape transcript evolution through selection pressures on interaction strength.

The paper compares disorder potential in natural and random sequences of prokaryotic and eukaryotic proteins, finding higher disorder near termini in eukaryotes and lower in prokaryotes, linked to functional sites.

The paper identifies an mRNA secondary structure that regulates translation re-initiation in bacteria, showing its conservation and differential enrichment across genomes.