Approaches to characterize structural properties of RNA
The secondary structure of an RNA molecule is fundamental for its function. However, structural conservation and the structure of RNA in vivo are still poorly understood. Data from recent high-throughput experiments can provide new insights, but they have not yet been systematically exploited. The a...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/665962 |
| Acceso en línea: | http://hdl.handle.net/10803/665962 |
| Access Level: | acceso abierto |
| Palabra clave: | RNA secondary structure IncRNAs Machine learning Structural conservation SHAPE Estructura secundaria ARN Conservación estructural 577 |
| Sumario: | The secondary structure of an RNA molecule is fundamental for its function. However, structural conservation and the structure of RNA in vivo are still poorly understood. Data from recent high-throughput experiments can provide new insights, but they have not yet been systematically exploited. The aim of my doctoral studies was to exploit these experimental data to develop computational approaches for discovering and analyzing structural properties of RNA. I developed two algorithms: CROSS predicts the secondary structure propensity profile of an RNA, and CROSSalign discovers structural similarities among different RNAs. In addition, I studied the effect of the presence of protein binding motifs on the prediction of the RNA structure, in vivo and investigated how the propensity of RNAs to bind to proteins could be exploited to create a predictive tool. The suite of tools that I developed opens new possibilities for studying the structural properties of long RNA molecules and for investigating structural conservation in large-scale analyses. |
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