Título:
Improving heterogeneous resolution in cryo-EM volumes reconstructions with pose refinement
Otros títulos:
Coordinador:
Director:
Compilador:
Autor:
Silvera Coeff, Diego
Tutor:
Lecumberry, Federico
Bartesaghi, Alberto
Bartesaghi, Alberto
Tipo de documento:
Tesis de maestría
Editor:
Palabras clave:
Cryo-electron microscopy (cryo-EM)
Heterogeneous 3D reconstruction
Deep generative models
Latent space analysis
UMAP
Clustering
Heterogeneous 3D reconstruction
Deep generative models
Latent space analysis
UMAP
Clustering
Descriptores:
Año de publicación:
2025
Contenido:
Resumen:
Single-particle cryo-electron microscopy (cryo-EM) has emerged as a transformative technique for determining the three-dimensional structures of macromolecular complexes at near-atomic resolution. Its ability to visualize biomolecules in multiple functional states without the need for crystallization has provided unprecedented insights into their structure, dynamics, and mechanisms, making it a cornerstone in structural biology and drug discovery. Despite its success, cryo-EM faces several challenges that limit the achievable resolution and accuracy of reconstructions. Chief among these are the inherently low signal-to-noise ratio (SNR) of raw micrographs, the difficulty in accurately estimating particle orientations (pose estimation), and the presence of conformational and compositional heterogeneity in the sample. In recent years, deep learning has emerged as a leading approach for addressing these limitations, offering powerful methods for denoising, pose refinement, and disentangling structural variability. In this work, a method designed to exploit particle heterogeneity for iterative pose refinement is presented. The approach integrates two state-of-the-art tools : cryoDRGN, which models structural variability using deep generative networks, and Frealign, which performs high-resolution 3D refinement. These tools were combined into a unified pipeline and tested on real cryo-EM datasets, demonstrating the potential of the method to improve both the accuracy of pose estimation and the quality of heterogeneous reconstructions.
Descripción:
Editorial:
Udelar.FI.
EN:
Financiadores:
Beca de Maestría ANII
Citación:
Silvera Coeff, D. Improving heterogeneous resolution in cryo-EM volumes reconstructions with pose refinement [en línea]. Tesis de maestría. Montevideo : Udelar. FI. IIE, 2025.
Citación:
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Documento del Gobiberno:
URI:
https://hdl.handle.net/20.500.12008/53431
ISBN:
e-ISBN:
ISSN:
1688-2806
ISMN:
Otros identificadores:
Título Obtenido:
Magíster en Ingeniería Eléctrica
Facultad o Servicio que otorga el Título:
Universidad de la República (Uruguay). Facultad de Ingeniería
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| Sil25.pdf | Tesis de maestría | 124.83 MB | Adobe PDF |