معرفی
Professor Tamir Tuller is a Full Professor in the Department of Biomedical Engineering at Tel Aviv University's Faculty of Engineering, where he leads the Laboratory of Computational Systems and Synthetic Biology. He also maintains affiliations with the Edmond J. Safra Center for Bioinformatics. His research spans computational biology, bioinformatics, and systems biology with a focus on developing mathematical models of gene expression and biological systems.
Prof. Tuller's research interests include computational modeling of gene expression, engineering of gene expression systems, deciphering the gene expression code, evolutionary systems biology, computational study of molecular evolution, and gene expression in diseases. His work particularly focuses on developing computational predictive models to mathematically analyze and simulate gene translation processes, devising approaches for engineering gene expression for biotechnological objectives, and analyzing large-scale genomic data to understand how gene expression is encoded in transcripts.
Analysis of his 15 most recent publications reveals a strong trend toward computational approaches for understanding and engineering biological systems. His work integrates mathematical modeling, machine learning, and large-scale genomic analysis to address challenges in virology, cancer research, synthetic biology, and genome editing. Key themes include the relationship between RNA structure and viral pathogenesis, computational prediction of CRISPR efficiency, AI-driven analysis of evolutionary patterns in codon usage, and the development of novel tools for gene expression modeling.
Prof. Tuller leads an active research laboratory focused on computational systems and synthetic biology. His team develops comprehensive computational models to study intracellular processes, particularly mRNA translation dynamics, and applies these models to problems in biotechnology, medicine, and agriculture. The lab's work bridges theoretical computational approaches with experimental validation, as evidenced by numerous publications demonstrating practical applications of their computational models.
His research has significant implications for vaccine development (particularly for viruses like Zika and Hepatitis C), cancer diagnostics and treatment, synthetic biology applications, and improving genome editing technologies. The lab's EXPosition tool for CRISPR-Cas9 sgRNA evaluation represents a practical application of their computational models that has potential to enhance genome editing projects across multiple fields.
