Bioinformatic analysis of catalytic DNA molecules
Functional Potential of Nucleic Acids
Abstract
Artificial evolution is a powerful method that makes it possible to isolate nucleic acids with specific functions (such as the ability to bind a ligand or catalyze a reaction) from large nucleic acid libraries. We have used this method for a variety of projects in our group, including to isolate catalytic DNA molecules (deoxyribozymes) that generate chemiluminescent, fluorescent, and colorimetric signals and to identify RNA-cleaving deoxyribozymes from structured nucleic acid libraries. High-throughput sequencing is an integral part our experimental workflow, and we are searching for a student with a background in bioinformatics who will help us to process these datasets. In addition to standard approaches such as motif mapping and secondary structure determination by covariation analysis, we are also interested in developing new methods. These include machine-learning based approaches to identify deoxyribozyme variants with new phenotypes.
Field of study: Bioinformatics
Universities
PhD students must be enrolled in a partner university and will be employed by the IOCB Prague at the same time (part-time or full time), which results in a competitive salary (a scholarship from the university + a salary from the IOCB). Each university has its own process, terms, and deadlines for PhD applications, which is separate from the IOCB recruitment process. You may discuss the details with the respective PI.
University partners
How to apply
Please return to the PhD projects at IOCB Prague – Call for Applications 2025 page and follow the instructions.