Translational research combining orthologous genes and human diseases with the OGOLOD dataset

OGOLOD is a Linked Open Data dataset derived from different biomedical resources by an automated pipeline, using a tailored ontology as a scaffold. The key contribution of OGOLOD is that it links, in new RDF triples, genetic human diseases and orthologous genes, paving the way for a more efficient translational biomedical research exploiting the Linked Open Data cloud

Publishing Orthology and Diseases Information in the Linked Open Data Cloud

The Linked Data initiative offers a straight method to publish structured data in the World Wide Web and link it to other data, resulting in a world wide network of semantically codified data known as the Linked Open Data cloud. The size of the Linked Open Data cloud, i.e. the amount of data published using Linked Data principles, is growing exponentially, including life sciences data. However, key information for biological research is still missing in the Linked Open Data cloud. For example, the relation between orthologs genes and genetic diseases is absent, even though such information can be used for hypothesis generation regarding human diseases. The OGOLOD system, an extension of the OGO Knowledge Base, publishes orthologs/diseases information using Linked Data. This gives the scientists the ability to query the structured information in connection with other Linked Data and to discover new information related to orthologs and human diseases in the cloud

Towards the semantic enrichment of Computer Interpretable Guidelines: a method for the identification of relevant ontological terms

Ponència presentada a 2018 The American Medical Informatics Association Annual Symposium (AMIA 2018) celebrat a San Francisco, Estats Units de l'Amèrica del Nord, el 3 de novembre de 2018Clinical Practice Guidelines (CPGs) contain recommendations intended to optimize patient care, produced based on a systematic review of evidence. In turn, Computer-Interpretable Guidelines (CIGs) are formalized versions of CPGs for use as decision-support systems. We consider the enrichment of the CIG by means of an OWL ontology that describes the clinical domain of the CIG, which could be exploited e.g. for the interoperability with the Electronic Health Record (EHR). As a first step, in this paper we describe a method to support the development of such an ontology starting from a CIG. The method uses an alignment algorithm for the automated identification of ontological terms relevant to the clinical domain of the CIG, as well as a web platform to manually review the alignments and select the appropriate ones. Finally, we present the results of the application of the method to a small corpus of CIGs

OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows

Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language for automating the changes to be performed in an ontology. OPPL augments the ontologists’ toolbox by providing a more efficient, and less error-prone, mechanism for enriching a biomedical ontology than that obtained by a manual treatment. Results We present OPPL-Galaxy, a wrapper for using OPPL within Galaxy. The functionality delivered by OPPL (i.e. automated ontology manipulation) can be combined with the tools and workflows devised within the Galaxy framework, resulting in an enhancement of OPPL. Use cases are provided in order to demonstrate OPPL-Galaxy’s capability for enriching, modifying and querying biomedical ontologies. Conclusions Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts. OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses

Tecnologías semánticas para la evaluación en red: análisis de una experiencia con la herramienta OeLE

The key role of Information and Communication Technology (ICT) in universities is out of question. The fast development of ICTs has brought with it the creation of new teaching-learning environments in higher education. This paper shows the results of a study that made use of a software in order to conduct and assess short-answer online tests. The software also provided students with feedback on their performance. The study was carried out with a group of undergraduate Education students at the University of Murcia (Spain) enrolled in an online subject. The focus of the online assessment procedures introduced in this study was beyond multiple-choice tests traditionally used in online assessment. Results of this study not only showed the scope of online assessment, but also defined guidelines for evaluation in online courses. This research study is part of the “Semantic Environment for Personalized Learning” Project funded by the Fundación Séneca (Murcia, Spain). No cuestionamos ya el importante papel que tienen las Tecnologías de la Información y la Comunicación (TIC) en nuestra realidad universitaria actual. El rápido devenir de estas herramientas ha supuesto la configuración de nuevos espacios de enseñanza-aprendizaje dentro de las distintas modalidades de enseñanza universitaria actuales. En este artículo se presentan los resultados de una investigación realizada tras la incorporación de un programa que permite realizar y corregir pruebas de evaluación de desarrollo a través de la red. Este programa permite hacer exámenes con preguntas de desarrollo y ofrece feedback al alumnado respecto a la prueba de evaluación realizada. Esta experiencia se llevó a cabo con un grupo de alumnos de la Licenciatura en Pedagogía de la Universidad de Murcia (España). Estos alumnos cursaban una asignatura optativa en red ofrecida por la titulación y se planteó la experiencia creando un entorno de evaluación en red que va más allá de las tradicionales pruebas tipo test utilizadas en los exámenes on-line. La finalidad de este análisis permite conocer no únicamente las posibilidades pedagógicas del entorno de evaluación en red, sino establecer además pautas de actuación para configurar futuros escenarios de evaluación en entornos virtuales con estas herramientas. Hemos de hacer constar que esta investigación ha sido realizada en el marco del Proyecto 08756/PI/08 “Plataforma Semántica de Formación a la Carta” financiado por la Fundación Séneca (Comunidad Autónoma de la Región de Murcia)

Evaluation of the OQuaRE framework for ontology quality

International audienceThe increasing importance of ontologies has resulted in the development of a large number of ontologies in both coordinated and non-coordinated efforts. The number and complexity of such ontologies make hard to ontology and tool developers to select which ontologies to use and reuse. So far, there are no mechanism for making such decisions in an informed manner. Consequently, methods for evaluating ontology quality are required. OQuaRE is a method for ontology quality evaluation which adapts the SQuaRE standard for software product quality to ontologies. OQuaRE has been applied to identify the strengths and weaknesses of different ontologies but, so far, this framework has not been evaluated itself. Therefore, in this paper we present the evaluation of OQuaRE, performed by an international panel of experts in ontology engineering. The results include the positive and negative aspects of the current version of OQuaRE, the completeness and utility of the quality metrics included in OQuaRE and the comparison between the results of the manual evaluations done by the experts and the ones obtained by a software implementation of OQuaRE

Flower transcriptional response to long term hot and cold environments in Antirrhinum majus

Short term experiments have identified heat shock and cold response elements in many biological systems. However, the effect of long-term low or high temperatures is not well documented. To address this gap, we grew Antirrhinum majus plants from two-weeks old until maturity under control (normal) (22/16°C), cold (15/5°C), and hot (30/23°C) conditions for a period of two years. Flower size, petal anthocyanin content and pollen viability obtained higher values in cold conditions, decreasing in middle and high temperatures. Leaf chlorophyll content was higher in cold conditions and stable in control and hot temperatures, while pedicel length increased under hot conditions. The control conditions were optimal for scent emission and seed production. Scent complexity was low in cold temperatures. The transcriptomic analysis of mature flowers, followed by gene enrichment analysis and CNET plot visualization, showed two groups of genes. One group comprised genes controlling the affected traits, and a second group appeared as long-term adaptation to non-optimal temperatures. These included hypoxia, unsaturated fatty acid metabolism, ribosomal proteins, carboxylic acid, sugar and organic ion transport, or protein folding. We found a differential expression of floral organ identity functions, supporting the flower size data. Pollinator-related traits such as scent and color followed opposite trends, indicating an equilibrium for rendering the organs for pollination attractive under changing climate conditions. Prolonged heat or cold cause structural adaptations in protein synthesis and folding, membrane composition, and transport. Thus, adaptations to cope with non-optimal temperatures occur in basic cellular processes

Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts

Introduction The secondary use of Electronic Healthcare Records (EHRs) often requires the identification of patient cohorts. In this context, an important problem is the heterogeneity of clinical data sources, which can be overcome with the combined use of standardized information models, Virtual Health Records, and semantic technologies, since each of them contributes to solving aspects related to the semantic interoperability of EHR data. Our main objective is to develop methods allowing for a direct use of EHR data for the identification of patient cohorts leveraging current EHR standards and semantic web technologies. Materials and Methods We propose to take advantage of the best features of working with EHR standards and ontologies. Our proposal is based on our previous results and experience working with both technological infrastructures. Our main principle is to perform each activity at the abstraction level with the most appropriate technology available. This means that part of the processing will be performed using archetypes (i.e., data level) and the rest using ontologies (i.e., knowledge level). Our approach will start working with EHR data in proprietary format, which will be first normalized and elaborated using EHR standards and then transformed into a semantic representation, which will be exploited by automated reasoning. Results We have applied our approach to protocols for colorectal cancer screening. The results comprise the archetypes, ontologies and datasets developed for the standardization and semantic analysis of EHR data. Anonymized real data has been used and the patients have been successfully classified by the risk of developing colorectal cancer. Conclusion This work provides new insights in how archetypes and ontologies can be effectively combined for EHR-driven phenotyping. The methodological approach can be applied to other problems provided that suitable archetypes, ontologies and classification rules can be designed.This work was supported by the Ministerio de Economia y Competitividad and the FEDER program through grants TIN2010-21388-C01 and TIN2010-21388-C02. MCLG was supported by the Fundacion Seneca through grant 15555/FPI/2010.Fernández-Breis, JT.; Maldonado Segura, JA.; Marcos, M.; Legaz-García, MDC.; Moner Cano, D.; Torres-Sospedra, J.; Esteban-Gil, A.... (2013). Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts. Journal of the American Medical Informatics Association. 20(E2):288-296. https://doi.org/10.1136/amiajnl-2013-001923S28829620E2Cuggia, M., Besana, P., & Glasspool, D. (2011). Comparing semi-automatic systems for recruitment of patients to clinical trials. International Journal of Medical Informatics, 80(6), 371-388. doi:10.1016/j.ijmedinf.2011.02.003Sujansky, W. (2001). Heterogeneous Database Integration in Biomedicine. Journal of Biomedical Informatics, 34(4), 285-298. doi:10.1006/jbin.2001.1024Schadow G Russler DC Mead CN . Integrating medical information and knowledge in the HL7 RIM. Proceedings of the AMIA Symposium, 2000:764–8.Johnson PD Tu SW Musen MA . A virtual medical record for guideline-based decision support. Proceedings of the AMIA 2001 Annual Symposium, 294–8.German, E., Leibowitz, A., & Shahar, Y. (2009). An architecture for linking medical decision-support applications to clinical databases and its evaluation. Journal of Biomedical Informatics, 42(2), 203-218. doi:10.1016/j.jbi.2008.10.007Peleg, M., Keren, S., & Denekamp, Y. (2008). Mapping computerized clinical guidelines to electronic medical records: Knowledge-data ontological mapper (KDOM). Journal of Biomedical Informatics, 41(1), 180-201. doi:10.1016/j.jbi.2007.05.003Maldonado, J. A., Costa, C. M., Moner, D., Menárguez-Tortosa, M., Boscá, D., Miñarro Giménez, J. A., … Robles, M. (2012). Using the ResearchEHR platform to facilitate the practical application of the EHR standards. Journal of Biomedical Informatics, 45(4), 746-762. doi:10.1016/j.jbi.2011.11.004Parker CG Rocha RA Campbell JR . Detailed clinical models for sharable, executable guidelines. Stud Health Technol Inform 2004;107:145–8.Clinical Information Modeling Initiative. http://informatics.mayo.edu/CIMI/index.php/Main_Page (accessed Jun 2013).W3C, OWL2 Web Ontology Language. http://www.w3.org/TR/owl2-overview/ (accessed Jun 2013).European Commission. Semantic interoperability for better health and safer healthcare. Deployment and research roadmap for Europe. ISBN-13: 978-92-79-11139-6, 2009.SemanticHealthNet. http://www.semantichealthnet.eu/ (accessed Jun 2013).Martínez-Costa, C., Menárguez-Tortosa, M., Fernández-Breis, J. T., & Maldonado, J. A. (2009). A model-driven approach for representing clinical archetypes for Semantic Web environments. Journal of Biomedical Informatics, 42(1), 150-164. doi:10.1016/j.jbi.2008.05.005Iqbal AM . An OWL-DL ontology for the HL7 reference information model. Toward useful services for elderly and people with disabilities Berlin: Springer, 2011:168–75.Tao, C., Jiang, G., Oniki, T. A., Freimuth, R. R., Zhu, Q., Sharma, D., … Chute, C. G. (2012). A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data. Journal of the American Medical Informatics Association, 20(3), 554-562. doi:10.1136/amiajnl-2012-001326Heymans, S., McKennirey, M., & Phillips, J. (2011). Semantic validation of the use of SNOMED CT in HL7 clinical documents. Journal of Biomedical Semantics, 2(1), 2. doi:10.1186/2041-1480-2-2Menárguez-Tortosa, M., & Fernández-Breis, J. T. (2013). OWL-based reasoning methods for validating archetypes. Journal of Biomedical Informatics, 46(2), 304-317. doi:10.1016/j.jbi.2012.11.009Lezcano, L., Sicilia, M.-A., & Rodríguez-Solano, C. (2011). Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules. Journal of Biomedical Informatics, 44(2), 343-353. doi:10.1016/j.jbi.2010.11.005Tao C Wongsuphasawat K Clark K . Towards event sequence representation, reasoning and visualization for EHR data. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium (IHI'12). New York, NY, USA: ACM:801–6.Bodenreider O . Biomedical ontologies in action: role in knowledge management, data integration and decision support. IMIA Yearbook of Medical Informatics 2008;67–79.Beale T . Archetypes. Constraint-based domain models for future-proof information systems. http://www.openehr.org/files/publications/archetypes/archetypes_beale_web_2000.pdfSNOMED-CT. http://www.ihtsdo.org/snomed-ct/ (accessed Jun 2013).UMLS Terminology Services. https://uts.nlm.nih.gov/home.html (accessed Jun 2013).The openEHR Foundation, openEHR Clinical Knowledge Manager. http://www.openehr.org/knowledge/ (accessed Jun 2013).Maldonado, J. A., Moner, D., Boscá, D., Fernández-Breis, J. T., Angulo, C., & Robles, M. (2009). LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics. International Journal of Medical Informatics, 78(8), 559-570. doi:10.1016/j.ijmedinf.2009.03.006SAXON XSLT and XQuery processor. http://saxon.sourceforge.net/ (accessed Jun 2013).NCBO Bioportal. http://bioportal.bioontology.org/ (accessed Jun 2013).The Protégé Ontology Editor and Knowledge Acquisition System. http://protege.stanford.edu/ (accessed Jun 2013).Semantic Web Integration Tool. http://sele.inf.um.es/swit (accessed Jun 2013).Hermit Reasoner. http://www.hermit-reasoner.com/ (accessed Jun 2013).The OWLAPI. http://owlapi.sourceforge.net/ (accessed Jun 2013).Institute for Health Metrics and Evaluation. Global Burden of Disease. http://www.healthmetricsandevaluation.org/gbd (accessed Jun 2013).Segnan N Patnick J von Karsa L . European guidelines for quality assurance in colorectal cancer screening and diagnosis 2010. First Edition. European Union. ISBN 978-92-79-16435-4.W3C. XQuery 1.0: An XML Query Language. http://www.w3.org/TR/xquery/ (accessed Jun 2013).DL Query. http://protegewiki.stanford.edu/wiki/DL_Query (accessed Jun 2013).SPARQL Query Language for RDF. http://www.w3.org/TR/rdf-sparql-query/ (accessed Jun 2013).Semantic Web Rule Language. http://www.w3.org/Submission/SWRL/ (accessed Jun 2013).Marcos, M., Maldonado, J. A., Martínez-Salvador, B., Boscá, D., & Robles, M. (2013). Interoperability of clinical decision-support systems and electronic health records using archetypes: A case study in clinical trial eligibility. Journal of Biomedical Informatics, 46(4), 676-689. doi:10.1016/j.jbi.2013.05.004Marcos, M., Maldonado, J. A., Martínez-Salvador, B., Moner, D., Boscá, D., & Robles, M. (2011). An Archetype-Based Solution for the Interoperability of Computerised Guidelines and Electronic Health Records. Lecture Notes in Computer Science, 276-285. doi:10.1007/978-3-642-22218-4_35MobiGuide: Guiding patients anytime everywhere. http://www.mobiguide-project.eu/ (accessed Jun 2013).EURECA: Enabling information re-Use by linking clinical RE search and Care. http://eurecaproject.eu/ (accessed Jun 2013).Rea, S., Pathak, J., Savova, G., Oniki, T. A., Westberg, L., Beebe, C. E., … Chute, C. G. (2012). Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: The SHARPn project. Journal of Biomedical Informatics, 45(4), 763-771. doi:10.1016/j.jbi.2012.01.009Clinical Element Models. http://informatics.mayo.edu/sharp/index.php/CEMS (accessed Jun 2013)

Using the ResearchEHR platform to facilitate the practical application of the EHR standards

Possibly the most important requirement to support co-operative work among health professionals and institutions is the ability of sharing EHRs in a meaningful way, and it is widely acknowledged that standardization of data and concepts is a prerequisite to achieve semantic interoperability in any domain. Different international organizations are working on the definition of EHR architectures but the lack of tools that implement them hinders their broad adoption. In this paper we present ResearchEHR, a software platform whose objective is to facilitate the practical application of EHR standards as a way of reaching the desired semantic interoperability. This platform is not only suitable for developing new systems but also for increasing the standardization of existing ones. The work reported here describes how the platform allows for the edition, validation, and search of archetypes, converts legacy data into normalized, archetypes extracts, is able to generate applications from archetypes and finally, transforms archetypes and data extracts into other EHR standards. We also include in this paper how ResearchEHR has made possible the application of the CEN/ISO 13606 standard in a real environment and the lessons learnt with this experience. © 2011 Elsevier Inc..This work has been partially supported by the Spanish Ministry of Science and Innovation under Grants TIN2010-21388-C02-01 and TIN2010-21388-C02-02, and by the Health Institute Carlos in through the RETICS Combiomed, RD07/0067/2001. Our most sincere thanks to the Hospital of Fuenlabrada in Madrid, including its Medical Director Pablo Serrano together with Marta Terron and Luis Lechuga for their support and work during the development of the medications reconciliation project.Maldonado Segura, JA.; Martínez Costa, C.; Moner Cano, D.; Menárguez-Tortosa, M.; Boscá Tomás, D.; Miñarro Giménez, JA.; Fernández-Breis, JT.... (2012). Using the ResearchEHR platform to facilitate the practical application of the EHR standards. Journal of Biomedical Informatics. 45(4):746-762. doi:10.1016/j.jbi.2011.11.004S74676245

Un entorno de integración de ontologías para el desarrollo de sistemas de gestión del conocimiento

El desarrollo de sistemas que faciliten la gestión de conocimiento es un elemento estratégico para las organizaciones en la actualidad. La necesidad de encontrar soluciones para obtener el conocimiento necesario para construir este tipo de sistemas ha sido la motivación primordial para esta tesis doctoral. La solución propuesta se basa en la mejora de los procesos de integración del conocimiento explicito disponible. Con ello, el desarrollo de sistemas para la gestión de conocimiento seria más eficiente. Dicho objetivo se ha logrado a través de las siguientes actividades: Definición y formalización de un entorno para la integración de ontologias Diseño e implementación de una aplicación software para el desarrollo cooperativo de ontologias Validación de la metodologia de construcción de ontologias Evaluación de la calidad de las ontologias obtenidas a través de los procesos de integración Evaluación de la utilidad de los procesos de integració