Seeking Grant Partners in Computational RNA Biology and Therapeutics

The COBRA Lab at the University of Alberta is seeking academic and industry partners to develop joint grant proposals connecting computational RNA biology with experimental validation and therapeutic applications. We welcome opportunities to build new collaborations or contribute computational expertise to existing research teams and consortia.

What we bring We develop algorithms to predict and compare RNA structures and structural ensembles, including complex pseudoknots and RNA–RNA interactions. Our approach combines physics-based modelling, structural abstraction, and AI/machine learning to investigate how RNA shape relates to function and to inform therapeutic target identification and molecular design. We can contribute computational methodology, custom software, biological data analysis, and the computational components of proposal development and project delivery.

Potential collaboration themes

• RNA structure and function: Investigating alternative conformations, regulatory elements, and the effects of sequence changes on RNA folding and biological activity.
• RNA therapeutics and vaccine design: Connecting structural predictions with experimental measurements to guide the design and evaluation of therapeutic RNAs.
• RNA interactions and targeting: Modelling RNA–RNA interactions and target accessibility to inform RNA-targeting strategies and functional RNA design.
• AI for RNA biology: Integrating physical principles, structural representations, and experimental data to develop and evaluate predictive models.

Partners we are seeking We are particularly interested in experimental groups with expertise in RNA biochemistry, structural probing or characterization, molecular biology, virology, RNA synthesis, or functional assays. Complementary computational and AI collaborators are also welcome.

Biotechnology and pharmaceutical partners could contribute application-driven research questions, candidate molecules, relevant datasets, experimental validation, or a pathway toward translation. Together, we would define a research programme in which computational predictions guide experiments and experimental findings improve the models.

Funding and collaboration model We are open to jointly identifying suitable national and international funding opportunities, including academic–industry collaborative research programmes. Contributions, leadership roles, budgets, data sharing, and intellectual property arrangements would be discussed during proposal development and aligned with institutional and funder requirements.

Timeline and next steps This opportunity is not tied to a single funding competition. We welcome both early-stage discussions and invitations to join proposals already in development. Submission and project timelines would be agreed with partners based on the selected programme and project readiness. An initial discussion would focus on the biological question, available data and experimental capabilities, complementary roles, and potential funding fit.