Geometry-aware template matching for cryo-electron tomograms in Dynamo

Template matching has a long history of serving as a tool for the automated analysis of volumes in cryo-electron tomography (cryo-ET). Recent theoretical and computational studies of the technique have pinpointed the importance of using fine angular samplings and high resolution scans to attain mean...

Descripción completa

Detalles Bibliográficos
Autores: Coray, Raffaele, Castaño-Díez, Daniel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/403396
Acceso en línea:http://hdl.handle.net/10261/403396
https://api.elsevier.com/content/abstract/scopus_id/105010970371
Access Level:acceso abierto
Palabra clave:Cryo-electron tomography
Local reconstruction
Subtomogram averaging
Template matching
Descripción
Sumario:Template matching has a long history of serving as a tool for the automated analysis of volumes in cryo-electron tomography (cryo-ET). Recent theoretical and computational studies of the technique have pinpointed the importance of using fine angular samplings and high resolution scans to attain meaningful results, thus highlighting the necessity of approaches that alleviate the computational burden inherent to this technique. We present the new module for model-aware template matching in Dynamo, an open-source tool that allows the integration of possibly available a priori information in the set-up of a template matching computation, leading-in favorable cases-to large computational gains, as the scanning effort can be more efficiently restricted to relevant spatial positions and dynamically defined angular orientations. This approach has been successfully tested on a representative range of sample geometries typically arising in tomography, modeling particles distributed over tubular, membranous, or vesicular structures.