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Showing 1–9 of 9 results
Advanced filters: Author: Ruben Sanchez-Garcia Clear advanced filters

  • Triadic interactions, where one node regulates the interaction between two others, are a ubiquitous form of higher-order interaction. Here, the authors show that triadic interactions modulate mutual information between linked nodes and propose an algorithm to mine them in real biological data.

    • Marta Niedostatek
    • Anthony Baptista
    • Ginestra Bianconi
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-11

  • Natural and synthetic networked systems can be characterized by synchrony or asynchrony of groups of their nodes (clusters) and undergo different scenarios of synchronization transitions. The authors propose an approach to predict the entire sequence of events that are taking place during the synchronization transition in networks of identical elements with any preferrable architecture.

    • Atiyeh Bayani
    • Fahimeh Nazarimehr
    • Stefano Boccaletti
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-11

  • Here, the authors present two local methods for analyzing cryo-EM maps: LocSpiral and LocBSharpen that enhance high-resolution features of cryoEM maps, while preventing map distortions. They also introduce LocBFactor and LocOccupancy, which allow obtaining local B-factors and electron density occupancy maps from cryo-EM reconstructions and the authors demonstrate that these methods improve the interpretability and analysis of cryo-EM maps using different test cases among them recent SARS-CoV-2 spike glycoprotein structures.

    • Satinder Kaur
    • Josue Gomez-Blanco
    • Javier Vargas
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-12

  • Sanchez-Garcia et al. present DeepEMhancer, a deep learning-based method that can automatically perform post-processing of raw cryo-electron microscopy density maps. The authors report that DeepEMhancer globally improves local quality of density maps, and may represent a useful tool for novel structures where PDB models are not readily available.

    • Ruben Sanchez-Garcia
    • Josue Gomez-Blanco
    • Javier Vargas
    ResearchOpen Access
    Communications Biology
    Volume: 4, P: 1-8

  • Gathering big datasets has become an essential component of machine learning in many scientific areas, but it is unavoidable that some data values are missing. An important and growing effect that needs careful attention, especially when heterogeneous data sources are combined, is that of structured missingness, where data values are missing not at random, but with a specific structure.

    • Robin Mitra
    • Sarah F. McGough
    • Ben D. MacArthur
    Reviews
    Nature Machine Intelligence
    Volume: 5, P: 13-23

  • Many real-world networks present structural symmetries that, while typically increasing robustness, deeply influence structural and dynamical properties. Here, the author studies the effect of symmetries on network measures and how they can be exploited to increase computational efficiency.

    • Rubén J. Sánchez-García
    ResearchOpen Access
    Communications Physics
    Volume: 3, P: 1-15