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| Hauptseite > Publikationsdatenbank > Influence of Contact Map Topology on RNA Structure Prediction |
| Hauptseite > Publikationsdatenbank > Influence of Contact Map Topology on RNA Structure Prediction |
| Poster (After Call) | FZJ-2023-05415 |
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2023
Abstract: The available sequence data of RNA molecules have highly increased in the past years. Unfortunately, while computational power is still under exponential growth, the computer prediction quality from sequence to final structure is still inferior to the labour intensive experimental work. Therefore, various attempts have been made to improve computer generated structure predictions.Although an end-to-end procedure has been developed for proteins in the form of Alphafold2, such a breakthrough is not yet available for RNA molecules. The current strategy entails two steps: (i) predicting potential contacts in the form of a contact maps from evolutionary data, and (ii) simulating the molecule with a physical force field while using the contact map as restraint. However, the quality of the structure prediction crucially depends on the quality of the contact map.Until now, only the proportion of true positive contacts was considered as a quality characteristic. We propose to also include the distribution of these contacts, and have done so in our recent studies. We observed that the distribution into clusters (typical for ML) leads to poor results. Therefore, we propose a new quality criterion for contact maps that can be easily incorporated into existing ML algorithms. We have introduced this criterion into Barnacle, a recent, very strong ML algorithm especially designed for RNA contact prediction.
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