Biology subjects

Conesa, P.

Publications and source records attributed to Conesa, P..

3 recordsLinked to original sources

bioRxiv2025

How many (distinguishable) classes can we identify in Single Particle Analysis?

Heterogeneity in cryoEM is essential for capturing macromolecule structural variability, reflecting their functional states and biological significance. However, estimating heterogeneity remains challenging due to particle misclassification and algorithmic biases, which can lead to reconstructions that blend distinct conformations or fail to resolve subtle differences. Furthermore, the low signal-to-noise ratio (SNR) inherent in cryo-EM data makes it nearly impossible to detect minute structural changes, as noise often obscures subtle variations in macromolecular projections. In this paper, we investigate the use of p-values associated with the null hypothesis that the observed classification differs from a random partition of the input dataset, thereby providing a statistical framework for determining the number of distinguishable classes present in a given dataset.

molecular biology↗

bioRxiv2020

FSC-Q: A CryoEM map-to-atomic model quality validation based on the local Fourier Shell Correlation

In recent years, advances in cryoEM have dramatically increased the resolution of Coulomb potential maps and, with it, the number of solved atomic models. It is widely accepted that the quality of cryoEM maps varies locally; therefore, the evaluation of the maps-derived structural models must be done locally as well. In this article, a method for the local analysis of the map-to-model fit is presented. The algorithm uses a comparison of two local resolution maps. The first is the local FSC (Fourier shell correlation) between the full map and the model, while the second is calculated between the half maps normally used in typical single particle analysis workflows. We call the new quality measure "FSC-Q", and it is a quantitative estimation of how much of the model is supported by the signal content of the map. Furthermore, we show that FSC-Q may be helpful to avoid overfitting. It can be used to complement other methods, such as the Q-score method that estimates the resolvability of atoms.

biophysics↗

bioRxiv2018

Automatic local resolution-based sharpening of cryo-EM maps.

Recent technological advances and computational developments, have allowed the reconstruction of cryo-EM maps at near-atomic resolution structures. Cryo-EM maps benefit significantly of a \"postprocessing\" step, normally referred to as \"sharpening\", that tends to increase signal at medium/high resolution. Here, we propose a new method for local sharpening of volumes generated by cryo-EM. The algorithm (LocalDeblur) is based on a local resolution-guided Wiener restoration approach, does not need any prior atomic model and it avoids artificial structure 1 factor corrections. LocalDeblur is fully automatic and parameter free. We show that the new method significantly and quantitatively improving map quality and interpretability, especially in cases of broad local resolution changes (as is often the case of membrane proteins).

biophysics↗