A Biocomputational Platform for Template-based Protein-protein Docking
We propose the creation of a Biocomputational Platform for template-based protein-protein docking that aims reduce computational time by clustering data before the rigid body alignment. Using data from the Dockground project, models will be created using multiple clustering methods that will annotat...
| Autores Principales: | Román-Brenes, Ricardo, Siles-Canales, Francisco, Zamora-Mata, Daniel |
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| Formato: | Artículo |
| Idioma: | Inglés |
| Publicado: |
Editorial Tecnológica de Costa Rica (entidad editora)
2020
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| Materias: | |
| Acceso en línea: |
https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/5084 https://hdl.handle.net/2238/12077 |
| Sumario: |
We propose the creation of a Biocomputational Platform for template-based protein-protein docking that aims reduce computational time by clustering data before the rigid body alignment. Using data from the Dockground project, models will be created using multiple clustering methods that will annotated each protein into a class, such that when performing the match search, not all of the databank needs to be inspected but just the class that resembles the most to the studied protein. This will reduce the time that conformation matching requires without incurring in lower precision. |
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