Map challenge: Analysis using a pair comparison method based on Fourier shell correlation

This document presents the analysis performed over the Map Challenge dataset using a new algorithm which we refer to as Pair Comparison Method. The new algorithm, which is described in detail in the text, is able to sort reconstructions based on a figure of merit and assigns a level of significance to the sorting. That is, it shows how likely the sorting is due to chance or if it reflects real differencesThe authors would like to acknowledge economical support from: The Spanish Ministry of Economy and Competitiveness through Grants BIO2013-44647-R, BIO2016-76400-R(AEI/FEDER, UE) and AEI/FEDER BFU 2016 74868P, the Comunidad Autónoma de Madrid through Grant: S2017/BMD-3817, European Union (EU) and Horizon 2020 through grant CORBEL (INFRADEV-1-2014-1, Proposal: 654248). This work used the EGI Infrastructure and is co-funded by the EGI-Engage project (Horizon 2020) under Grant No. 654142. European Union (EU) and Horizon 2020 through grant West-Life (EINFRA-2015-1, Proposal: 675858) European Union (EU) and Horizon 2020 through grant Elixir - EXCELERATE (INFRADEV-3-2015, Proposal: 676559) European Union (EU) and Horizon 2020 through grant iNEXT (INFRAIA-1–2014-2015, Proposal: 653706). The authors acknowledge the support and the use of resources of Instruct, a Landmark ESFRI projec

Quantitative morphometrical characterization of human pronuclear zygotes

BACKGROUND Identification of embryos with high implantation potential remains a challenge in in vitro fertilization (IVF). Subjective pronuclear (PN) zygote scoring systems have been developed for that purpose. The aim of this work was to provide a software tool that enables objective measuring of morphological characteristics of the human PN zygote. METHODS A computer program was created to analyse zygote images semi-automatically, providing precise morphological measurements. The accuracy of this approach was first validated by comparing zygotes from two different IVF centres with computer-assisted measurements or subjective scoring. Computer-assisted measurement and subjective scoring were then compared for their ability to classify zygotes with high and low implantation probability by using a linear discriminant analysis. RESULTS Zygote images coming from the two IVF centres were analysed with the software, resulting in a series of precise measurements of 24 variables. Using subjective scoring, the cytoplasmic halo was the only feature which was significantly different between the two IVF centres. Computer-assisted measurements revealed significant differences between centres in PN centring, PN proximity, cytoplasmic halo and features related to nucleolar precursor bodies distribution. The zygote classification error achieved with the computer-assisted measurements (0.363) was slightly inferior to that of the subjective ones (0.393). CONCLUSIONS A precise and objective characterization of the morphology of human PN zygotes can be achieved by the use of an advanced image analysis tool. This computer-assisted analysis allows for a better morphological characterization of human zygotes and can be used for classificatio

Framework for automatic generation of ontology mappings

Some of the most outstanding problems in Computer Science (e.g. access to heterogeneous information sources, use of different e-commerce standards, ontology translation, etc.) are often approached through the identification of ontology mappings. A manual mapping generation slows down, or even makes unfeasible, the solution of particular cases of the aforementioned problems via ontology mappings. Some algorithms and formal models for partial tasks of automatic generation of mappings have been proposed. However, an integrated framework to solve this problem is still missing. In this paper, we present a framework for automatic ontology mapping generation, and a partial implementation of it. Our proposal is that this integrated vision can guide, not only our future work, but also the future work of other researchers. In the implementation carried out, we have built a mapping ontology with knowledge on ontology mappings

Flexible workflows for on-the-fly electronmicroscopy single-particle image processing using Scipion

Electron microscopy of macromolecular structures is an approach that is in increasing demand in the field of structural biology. The automation of image acquisition has greatly increased the potential throughput of electron microscopy. Here, the focus is on the possibilities in Scipion to implement flexible and robust image-processing workflows that allow the electron-microscope operator and the user to monitor the quality of image acquisition, assessing very simple acquisition measures or obtaining a first estimate of the initial volume, or the data resolution and heterogeneity, without any need for programming skills. These workflows can implement intelligent automatic decisions and they can warn the user of possible acquisition failures. These concepts are illustrated by analysis of the well known 2.2 Å resolution β-galactosidase data setThe authors would like to acknowledge financial support from The Spanish Ministry of Economy and Competitiveness through the BIO2016-76400-R (AEI/FEDER, UE) grant, the Comunidad Auto´noma de Madrid through grant S2017/BMD3817, the Instituto de Salud Carlos III (PT17/0009/0010), the European Union (EU) and Horizon 2020 through the CORBEL grant (INFRADEV-1-2014-1, Proposal 654248), the ‘la Caixa’ Foundation (ID 100010434, Fellow LCF/BQ/ IN18/11660021), Elixir–EXCELERATE (INFRADEV-3- 2015, Proposal 676559), iNEXT (INFRAIA-1-2014-2015, Proposal 653706), EOSCpilot (INFRADEV-04-2016, Proposal 739563) and INSTRUCT–ULTRA (INFRADEV03-2016-2017, Proposal 731005

Fast, robust, and accurate determination of transmission electron microscopy contrast transfer function

International audienceTransmission electron microscopy, as most imaging devices, introduces optical aberrations that in the case of thin specimens are usu- ally modeled in Fourier space by the so-called contrast transfer function (CTF). Accurate determination of the CTF is crucial for its posterior correction. Furthermore, the CTF estimation must be fast and robust if high-throughput three-dimensional electron micros- copy (3DEM) studies are to be carried out. In this paper we present a robust algorithm that fits a theoretical CTF model to the power spectrum density (PSD) measured on a specific micrograph or micrograph area. Our algorithm is capable of estimating the envelope of the CTF which is absolutely needed for the correction of the CTF amplitude changes