Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline. The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project. The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.
In the framework of forensic anthropology osteometric techniques are generally preferred over visual examinations due to a higher level of reproducibility and repeatability; qualities that are crucial within a legal context. The use of osteometric methods has been further reinforced by incorporating statistically-based algorithms and large reference samples in a variety of user-friendly software applications. However, the continued increase in admixture of human populations have made the use of osteometric methods for estimation of ancestry much more complex, which confounds one of major requirements of ancestry assessment - intra-population homogeneity. The present paper tests the accuracy of ancestry and sex assessment using four identification software tools, specifically FORDISC 2.0, FORDISC 3.1.293, COLIPR 1.5.2 and 3D-ID 1.0. Software accuracy was tested in a sample of 174 documented human crania of Brazilian origin composed of different ancestral groups (i.e., European Brazilians, Afro-Brazilians, and Japanese Brazilians and of admixed ancestry). The results show that regardless of the software algorithm employed and composition of the reference database, all methods were able to allocate approximately 50% of Brazilian specimens to an appropriate major reference group. Of the three ancestral groups, Afro-Brazilians were especially prone to misclassification. Japanese Brazilians, by contrast, were shown to be relatively easily recognizable as being of Asian descent but at the same time showed a strong affinity towards Hispanic crania, in particularly when the classification based on FDB was carried out in FORDISC. For crania of admixed origin all of the algorithms showed a considerable higher rate of inconsistency with a tendency for misclassification into Asian and American Hispanic groups. Sex assessments revealed an overall modest to poor reliability (60-71% of correctly classified specimens) using the tested software programs with unbalanced individual rates for males and females. The highest and atypically balanced rate of classification for sex assessment was provided by COLIPR software, which reached 78% of correctly assessed crania.
- MeSH
- Humans MeSH
- Population Groups ethnology MeSH
- Software standards MeSH
- Forensic Anthropology * methods MeSH
- Sex Determination by Skeleton methods MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Validation Study MeSH
- Geographicals
- Brazil MeSH
Non-coding RNAs (ncRNA) are essential for all life, and their functions often depend on their secondary (2D) and tertiary structure. Despite the abundance of software for the visualisation of ncRNAs, few automatically generate consistent and recognisable 2D layouts, which makes it challenging for users to construct, compare and analyse structures. Here, we present R2DT, a method for predicting and visualising a wide range of RNA structures in standardised layouts. R2DT is based on a library of 3,647 templates representing the majority of known structured RNAs. R2DT has been applied to ncRNA sequences from the RNAcentral database and produced >13 million diagrams, creating the world's largest RNA 2D structure dataset. The software is amenable to community expansion, and is freely available at https://github.com/rnacentral/R2DT and a web server is found at https://rnacentral.org/r2dt .
- MeSH
- Databases, Nucleic Acid MeSH
- Nucleic Acid Conformation MeSH
- RNA, Untranslated chemistry MeSH
- Reproducibility of Results MeSH
- RNA chemistry MeSH
- Sequence Analysis, RNA MeSH
- Software MeSH
- Computational Biology methods MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Intramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
ELIXIR is a pan-European intergovernmental organisation for life science that aims to coordinate bioinformatics resources in a single infrastructure across Europe; bioinformatics training is central to its strategy, which aims to develop a training community that spans all ELIXIR member states. In an evidence-based approach for strengthening bioinformatics training programmes across Europe, the ELIXIR Training Platform, led by the ELIXIR EXCELERATE Quality and Impact Assessment Subtask in collaboration with the ELIXIR Training Coordinators Group, has implemented an assessment strategy to measure quality and impact of its entire training portfolio. Here, we present ELIXIR's framework for assessing training quality and impact, which includes the following: specifying assessment aims, determining what data to collect in order to address these aims, and our strategy for centralised data collection to allow for ELIXIR-wide analyses. In addition, we present an overview of the ELIXIR training data collected over the past 4 years. We highlight the importance of a coordinated and consistent data collection approach and the relevance of defining specific metrics and answer scales for consortium-wide analyses as well as for comparison of data across iterations of the same course.
- MeSH
- Algorithms MeSH
- Biomedical Research MeSH
- Databases, Factual MeSH
- Program Evaluation MeSH
- Education, Continuing MeSH
- Curriculum MeSH
- Reproducibility of Results MeSH
- Quality Control * MeSH
- Data Collection MeSH
- Software MeSH
- User-Computer Interface MeSH
- Computational Biology education standards MeSH
- Research Personnel MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Europe MeSH
Benchmarking and monitoring of urban design and transport features is crucial to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that either only allow between-city comparisons, or require expensive, technical, local spatial analyses for within-city comparisons. This study developed a reusable, open-source urban indicator computational framework using open data to enable consistent local and global comparative analyses. We show this framework by calculating spatial indicators-for 25 diverse cities in 19 countries-of urban design and transport features that support health and sustainability. We link these indicators to cities' policy contexts, and identify populations living above and below critical thresholds for physical activity through walking. Efforts to broaden participation in crowdsourcing data and to calculate globally consistent indicators are essential for planning evidence-informed urban interventions, monitoring policy effects, and learning lessons from peer cities to achieve health, equity, and sustainability goals.
- MeSH
- Global Health * MeSH
- Humans MeSH
- Spatial Analysis MeSH
- Software MeSH
- Cities MeSH
- Health Status * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, P.H.S. MeSH
- Geographicals
- Cities MeSH
Advances in cryo-electron microscopy (cryo-EM) have made it possible to obtain structures of large biological macromolecules at near-atomic resolution. This "resolution revolution" has encouraged the use and development of modeling tools able to produce high-quality atomic models from cryo-EM density maps. Unfortunately, many practical problems appear when combining different packages in the same processing workflow, which make difficult the use of these tools by non-experts and, therefore, reduce their utility. We present here a major extension of the image processing framework Scipion that provides inter-package integration in the model building area and full tracking of the complete workflow, from image processing to structure validation.
Fast Photochemical Oxidation of Proteins (FPOP) is a promising technique for studying protein structure and dynamics. The quality of insight provided by FPOP depends on the reliability of the determination of the modification site. This study investigates the performance of two search engines, Mascot and PEAKS, for the data processing of FPOP analyses. Comparison of Mascot and PEAKS of the hemoglobin--haptoglobin Bruker timsTOF data set (PXD021621) revealed greater consistency in the Mascot identification of modified peptides, with around 26% of the IDs being mutual for all three replicates, compared to approximately 22% for PEAKS. The intersection between Mascot and PEAKS results revealed a limited number (31%) of shared modified peptides. Principal Component Analysis (PCA) using the peptide-spectrum match (PSM) score, site probability, and peptide intensity was applied to evaluate the results, and the analyses revealed distinct clusters of modified peptides. Mascot showed the ability to assess confident site determination, even with lower PSM scores. However, high PSM scores from PEAKS did not guarantee a reliable determination of the modification site. Fragmentation coverage of the modification position played a crucial role in Mascot assignments, while the AScore localizations from PEAKS often become ambiguous because the software employs MS/MS merging.
The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.
- Publication type
- Journal Article MeSH
