Speaker: Can Cenik, PhD
Tenured Associate Professor at University of Texas at Austin
Department of Molecular Biosciences
About the Seminar
“An Integrative Approach to Predictive Modeling and Single-Cell Measurements of Translation”
My laboratory investigates how translation determines protein abundance through predictive modeling and development of novel measurement technologies. We pioneered a technique that uses the principles of microfluidics and isotachophoresis that we named Ribo-ITP. This innovation enables high resolution measurement of translation in scarce biological samples including single cells, opening new avenues in developmental biology, neuroscience and cancer research.
In our computational work, we compiled measurements of translation from more than 3,500 experiments. We introduced the concept of translation efficiency covariation (TEC), showing that transcripts with shared biological functions and those that are members of the same protein complexes exhibit TEC. We used our compendium of translation efficiency measurements to develop a deep neural network model called RiboNN that predicts mRNA translation rates across many cell types from the full length mRNA sequence. RiboNN is the most accurate predictive tool of translation efficiency.
It can evaluate the impact of genetic variants in the human population and provide insight into diseases driven by abnormal mRNA translation. We are excited to apply these advances in bioengineering, genetic diagnostics and the design and optimization of mRNA therapies.
Event Details
- Date: February 2, 2026
- Time: 11:30 a.m. – 12:30 p.m.
- Location: BST3 6014