Comparar métodos

	Reconstrucción por crio-microscopía electrónica	Modelado por Homología	Topología de Redes de Interacción Proteína-Proteína (PPI)
Campo	Bioinformática	Bioinformática	Bioinformática
Familia	Process / pipeline	Process / pipeline	Process / pipeline
Año de origen	1975	1993	2000
Autor original	Joachim Frank	Andrej Sali	Peter Uetz
Tipo	Image reconstruction pipeline	Comparative structure prediction pipeline	Network analysis pipeline
Fuente seminal	Frank, J. (2002). Single-particle imaging of macromolecules by cryo-electron microscopy. Annual Review of Biophysics and Biomolecular Structure, 31, 303-319.	Sali, A. & Blundell, T. L. (1993). Comparative protein modelling by satisfaction of spatial restraints. Journal of Molecular Biology, 234(3), 779-815.	Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., ... & Lomax, J. (2000). A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature, 403(6770), 623-627.
Alias	cryo-electron microscopy, cryo-EM, single-particle cryo-EM	comparative modeling, template-based modeling	protein interaction networks, interactome analysis, network topology
Relacionados	3	4	3
Resumen	Cryo-electron microscopy (cryo-EM) determines three-dimensional macromolecular structures at atomic or near-atomic resolution by imaging proteins frozen in vitreous ice. Pioneered by Frank, Henderson, and others, this technique has revolutionized structural biology by enabling visualization of large, non-crystallizable complexes and capturing functional conformational states.	Homology modeling, also called comparative modeling, predicts the three-dimensional structure of a protein using an experimentally-solved structure of a homologous protein as a template. Introduced by Sali and Blundell in 1993, this method exploits the principle that homologous proteins share similar spatial structures despite differing in amino acid sequence.	Protein-protein interaction network analysis identifies and characterizes the structural properties of cellular interaction networks. Pioneered by Uetz and colleagues through large-scale yeast two-hybrid screening, this approach reveals topological features like hubs, modules, and motifs that encode functional organization and disease associations.