A systematic literature review on the development and use of mobile learning (web) apps by early adopters

Surveys in mobile learning developed so far have analysed in a global way the effects on the usage of mobile devices by means of general apps or apps already developed. However, more and more teachers are developing their own apps to address issues not covered by existing m-learning apps. In this article, by means of a systematic literature review that covers 62 publications placed in the hype of teacher-created m-learning apps (between 2012 and 2017, the early adopters) and the usage of 71 apps, we have analysed the use of specific m-learning apps. Our results show that apps have been used both out of the classroom to develop autonomous learning or field trips, and in the classroom, mainly, for collaborative activities. The experiences analysed only develop low level outcomes and the results obtained are positive improving learning, learning performance, and attitude. As a conclusion of this study is that the results obtained with specific developed apps are quite similar to previous general surveys and that the development of long-term experiences are required to determine the real effect of instructional designs based on mobile devices. These designs should also be oriented to evaluate high level skills and take advantage of mobile features of mobile devices to develop learning activities that be made anytime at anyplace and taking into account context and realistic situations. Furthermore, it is considered relevant the study of the role of educational mobile development frameworks in facilitating teachers the development of m-learning apps

Obteniendo respuestas de repositorios semánticos usando palabras clave

The Web of Data proposes to publish and connect data by applying the semantic web technologies for the representation of knowledge and data and the definition of queries. The success of the Web of Data requires that both humans and machines are able to extract information from such semantic repositories. For this purpose, query interfaces for humans must make the interaction with the repository as transparent as possible. In this work, we present a generic method for querying semantic repositories based on processing and recognizing the keywords input by the users as entities of the ontology used in the description of the data. A SPARQL query is automatically derived from the query graph extracted from the list of keywords. We also describe the application of the method to three different semantic repositories from different domains.La Web de Datos propone publicar y conectar los datos utilizando las tecnologías de la web semántica para la representación del conocimiento, de los datos y la especificación de consultas. El éxito de la Web de Datos requiere que tanto los humanos como las máquinas sean capaces de obtener información en estos repositorios semánticos. Para ello, los interfaces de consulta para humanos deben hacer lo más transparente posible el proceso de interacción con el repositorio. En este trabajo presentamos un método genérico para la consulta de repositorios semánticos basado en el reconocimiento de las keywords introducidas por los usuarios como entidades de la ontología utilizada para la descripción de los datos. Del procesamiento del grafo de consulta generado se deriva automáticamente la consulta SPARQL que se ejecuta contra el repositorio. Describimos el uso del método con tres repositorios de distintos dominios.This work has been funded by the Spanish Ministry of Economy, Industry and Competitiveness, the European Regional Development Fund (ERDF) Programme and the Fundación Séneca through grants TIN2014-53749-C2-2-R and 19371/PI/14

OntoEnrich: A platform for the lexical analysis of ontologies focused on their axiomatic enrichment

OntoEnrich es una plataforma online para la detección automática y análisis de regularidades léxicas encontradas en las etiquetas asociadas a los conceptos de una ontología. Un análisis guiado por estas regularidades permite explorar diferentes aspectos léxico/semánticos, como puede ser la aplicación de los principios del OBO Foundry en el caso de ontologías biomédicas. El objetivo de esta demostración es presentar casos de uso obtenidos al aplicar la herramienta en ontologías relevantes como Gene Ontology o SNOMED CT. Mostraremos cómo dicho análisis permite identificar semántica oculta a partir de contenido descrito en lenguaje natural (apto para humanos), y cómo podría ser usado para enriquecer la ontología creando nuevos axiomas lógicos (aptos para máquinas).We present OntoEnrich, an online platform for the automatic detection and guided analysis of lexical regularities in ontology labels. An analysis guided by these regularities permits users to explore different lexical and semantic aspects as the application of the OBO Foundry principles in biomedical ontologies. The goal of this demonstration is to show some use cases obtained after applying OntoEnrich in two relevant biomedical ontologies such as Gene Ontology and SNOMED CT. Thus, we will show how the performed analysis could be used to elucidate hidden semantics from the natural language fragments (human-friendly), and how this could be used to enrich the ontology by generating new logical axioms (machine-friendly).Este trabajo ha sido posible gracias al Ministerio de Economía y Competitividad y el Fondo Europeo de Desarrollo Regional (FEDER), a través del proyecto TIN2014-53749-C2-2-R, y a la Fundación Séneca a través del proyecto 19371/PI/14

LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics

Purpose To develop a powerful archetype editing framework capable of handling multiple reference models and oriented towards the semantic description and standardization of legacy data. Methods The main prerequisite for implementing tools providing enhanced support for archetypes is the clear specification of archetype semantics. We propose a formalization of the definition section of archetypes based on types over tree-structured data. It covers the specialization of archetypes, the relationship between reference models and archetypes and conformance of data instances to archetypes. Results LinkEHR-Ed, a visual archetype editor based on the former formalization with advanced processing capabilities that supports multiple reference models, the editing and semantic validation of archetypes, the specification of mappings to data sources, and the automatic generation of data transformation scripts, is developed. Conclusions LinkEHR-Ed is a useful tool for building, processing and validating archetypes based on any reference model.This work was supported in part by the Spanish Ministry of Education and Science under grant TS12007-66S7S-C02; by the Generalitat Valenciana under grant APOSTD/2007/055 and by the program PAID-06-07 de la Universidad Politecnica de Valencia.Maldonado Segura, JA.; Moner Cano, D.; Boscá Tomás, D.; Fernandez Breis, JT.; Angulo Fernández, C.; Robles Viejo, M. (2009). LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics. International Journal of Medical Informatics. 78(8):559-570. https://doi.org/10.1016/j.ijmedinf.2009.03.006S55957078

Improvement of large copy number variant detection by whole genome nanopore sequencing

Introduction: Whole-genome sequencing using nanopore technologies can uncover structural variants, which are DNA rearrangements larger than 50 base pairs. Nanopore technologies can also characterize their boundaries with single-base accuracy, owing to the kilobase-long reads that encompass either full variants or their junctions. Other methods, such as next-generation short read sequencing or PCR assays, are limited in their capabilities to detect or characterize structural variants. However, the existing software for nanopore sequencing data analysis still reports incomplete variant sets, which also contain erroneous calls, a considerable obstacle for the molecular diagnosis or accurate genotyping of populations. Methods: We compared multiple factors affecting variant calling, such as reference genome version, aligner (minimap2, NGMLR, and lra) choice, and variant caller combinations (Sniffles, CuteSV, SVIM, and NanoVar), to find the optimal group of tools for calling large (>50 kb) deletions and duplications, using data from seven patients exhibiting gross gene defects on SERPINC1 and from a reference variant set as the control. The goal was to obtain the most complete, yet reasonably specific group of large variants using a single cell of PromethION sequencing, which yielded lower depth coverage than short-read sequencing. We also used a custom method for the statistical analysis of the coverage value to refine the resulting datasets. Results: We found that for large deletions and duplications (>50 kb), the existing software performed worse than for smaller ones, in terms of both sensitivity and specificity, and newer tools had not improved this. Our novel software, disCoverage, could polish variant callers’ results, improving specificity by up to 62% and sensitivity by 15%, the latter requiring other data or samples. Conclusion: We analyzed the current situation of >50-kb copy number variants with nanopore sequencing, which could be improved. The methods presented in this work could help to identify the known deletions and duplications in a set of patients, while also helping to filter out erroneous calls for these variants, which might aid the efforts to characterize a not-yet well-known fraction of genetic variability in the human genome

ColPortal, an integrative multiomic platform for analysing epigenetic interactions in colorectal cancer

Abstract Colorectal cancer (CRC) is the third leading cause of cancer mortality worldwide. Different pathological pathways and molecular drivers have been described and some of the associated markers are used to select effective anti-neoplastic therapy. More recent evidence points to a causal role of microbiota and altered microRNA expression in CRC carcinogenesis, but their relationship with pathological drivers or molecular phenotypes is not clearly established. Joint analysis of clinical and omics data can help clarify such relations. We present ColPortal, a platform that integrates transcriptomic, microtranscriptomic, methylomic and microbiota data of patients with colorectal cancer. ColPortal also includes detailed information of histological features and digital histological slides from the study cases, since histology is a morphological manifestation of a complex molecular change. The current cohort consists of Caucasian patients from Europe. For each patient, demographic information, location, histology, tumor staging, tissue prognostic factors, molecular biomarker status and clinical outcomes are integrated with omics data. ColPortal allows one to perform multiomics analyses for groups of patients selected by their clinical data

The gene regulation knowledge commons: the action area of GREEKC

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various steps in the knowledge management process that focuses on understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to standardize and update existing knowledge management workflows and involve end-users in the process of designing the Gene Regulation Knowledge Commons (GRKC). Here the GREEKC consortium describes its main achievements in improving this GRKC.info:eu-repo/semantics/publishedVersio

Eosinophils Reduce Chronic Inflammation in Adipose Tissue by Secreting Th2 Cytokines and Promoting M2 Macrophages Polarization

Obesity is now recognized as a low-grade, chronic inflammatory disease that is linked to a myriad of disorders including cardiovascular diseases, type 2 diabetes, and liver diseases. Recently it is found that eosinophils accelerate alternative activation macrophage (AAM) polarization by secreting Th2 type cytokines such as interleukin-4 and interleukin-13, thereby reducing metainflammation in adipose tissue. In this review, we focused on the role of eosinophils in regulating metabolic homeostasis and obesity

BioHackathon 2015: Semantics of data for life sciences and reproducible research.

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web