Estudio metabolómico en tejido prostático y orina para el diagnóstico y pronóstico del cáncer de próstata

La metabolómica es una ciencia que brinda la oportunidad de obtener biomarcadores para el cáncer de próstata de manera no invasiva. A partir de pacientes que acudían a realizarse una biopsia transrectal de próstata, se obtuvieron muestras de tisulares de cilindros prostáticos y muestras de orina por micción espontánea tras masaje prostático. Tras adquirir todos los espectros mediante un espectrómetro Bruker Avance III DRX 600, las muestras de tejido se sometieron a estudio histológico habitual en el Servicio de Anatomía Patológica, estableciendo la presencia o no de cáncer de próstata. Se realizaron análisis con metabolitos y variables clínicas con el objetivo de predecir la presencia y pronóstico del cáncer de próstata, recogiéndose datos de 201 pacientes. Según el análisis con sonda HR-MAS, metabolitos detectados en tejido como el citrato o el glicerol-3-fosfoclina, junto con el volumen prostático y el tacto rectal sospechoso, formaban un modelo predictor de cáncer prostático en tejido con un área bajo la curva (AUC) de 0,87, una especificidad del 94%, un valor predictivo positivo (VPP) del 80% y un valor predictivo negativo (VPN) del 84%. Por otra parte, el análisis HR-MAS permitió crear un modelo predictor para detectar grados de Gleason 8 o mayores con metabolitos del metabolismo del glutatión y de aminoácidos que, junto con el tacto rectal, alcanzaba un AUC de 0,90, una sensibilidad del 87%, un VPP del 82% y un VPN del 80%. Por último, el análisis HR-MAS para predecir casos con recidiva bioquímica, estableció que moléculas principalmente del metabolismo de glicina, serina, treonina o de la glicólisis, establecían un modelo con un AUC de 0,87, con una especificidad del 93%, un VPP del 44% y un VPN del 84%. En el análisis metabolómico en orina, el modelo con capacidad de predecir la presencia de cáncer concluyó que partículas del metabolismo de la glicólisis, glicerofosfolípido, y de algunos aminoácidos, junto con el volumen prostático y la sospecha ecográfica tumoral, aportaba un AUC de 0,89, con un VPP del 82% y un VPN del 83%. Por su parte, metabolitos de la glicólisis, del metabolismo de aminoácidos y del ciclo de Krebs, junto con el tacto rectal sospechoso, formaban un modelo predictor con un AUC de 0,92, con una sensibilidad del 82% y una especificidad del 92%, para localizar tumores con Gleason elevado. Además, abundantes moléculas en orina del metabolismo de aminoácidos, permitieron crear un modelo con un AUC de 0,95, sensibilidad del 80% y especificidad del 98% para predecir recidiva bioquímica. Así pues, La metabolómica, mediante análisis HR-MAS es capaz de hallar una huella metabólica específica de cáncer de próstata en tejido prostático, siento útil para el diagnóstico y pronóstico, y utilizando sólo un cilindro tisular obtenido mediante biopsia transrectal. Por otra parte, mediante análisis metabolómico en orina se han hallado múltiples metabolitos que, combinados con variables clínicas, son útiles en este contexto

Medición Temprana de la Usabilidad en Ambientes OO-Method

En este documento se presenta la instanciación de un método de evaluación de la usabilidad para OO-Method, un entorno de generación automática de código a partir de Modelos Conceptuales. El propósito de este trabajo es el de proporcionar un mecanismo para evaluar la usabilidad del sistema a partir de su Modelo Conceptual.Panach Navarrete, JI. (2007). Medición Temprana de la Usabilidad en Ambientes OO-Method. http://hdl.handle.net/10251/12913Archivo delegad

Defining Interaction Design Patterns to Extract Knowledge from Big Data

[EN] The Big Data domain offers valuable opportunities to gain valuable knowledge. The User Interface (UI), the place where the user interacts to extract knowledge from data, must be adapted to address the domain complexities. Designing UIs for Big Data becomes a challenge that involves identifying and designing the user-data interaction implicated in the knowledge extraction. To design such an interaction, one widely used approach is design patterns. Design Patterns describe solutions to common interaction design problems. This paper proposes a set of patterns to design UIs aimed at extracting knowledge from the Big Data systems data conceptual schemas. As a practical example, we apply the patterns to design UI s for the Diagnosis of Genetic Diseases domain since it is a clear case of extracting knowledge from a complex set of genetic data. Our patterns provide valuable design guidelines for Big Data UIs.The authors thank the members of the PROS Center's Genome group for fruitful discussions. In addition, it is also important to highlight that Secretaria Nacional de Educacion, Ciencia y Tecnologia (SENESCYT) and Escuela Politecnica Nacional from Ecuador have supported this work. This project also has the support of Generalitat Valenciana through project IDEO (PROMETEOII/2014/039) and Spanish Ministry of Science and Innovation through project DataME (ref: TIN2016-80811-P).Iñiguez Jarrín, CE.; Panach Navarrete, JI.; Pastor López, O. (2018). Defining Interaction Design Patterns to Extract Knowledge from Big Data. Springer. 490-504. https://doi.org/10.1007/978-3-319-91563-0_30S490504Power, D.J.: ‘Big Data’ decision making use cases. In: Delibašić, B., Hernández, J.E., Papathanasiou, J., Dargam, F., Zaraté, P., Ribeiro, R., Liu, S., Linden, I. (eds.) ICDSST 2015. LNBIP, vol. 216, pp. 1–9. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-18533-0_1Genetic Alliance: Capítulo 2, Diagnóstico de una enfermedad genética (2009). https://www.ncbi.nlm.nih.gov/books/NBK132200/Pabinger, S., et al.: A survey of tools for variant analysis of next-generation genome sequencing data. Brief Bioinform. 15(2), 256–278 (2014). https://doi.org/10.1093/bib/bbs086Borchers, J.O.: Pattern approach to interaction design. In: Proceedings of the Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques, DIS 2000, pp. 369–378 (2000)Tidwell, J.: Designing Interfaces, vol. XXXIII, no. 2. O’Reilly Media, Sebastopol (2012)Van Duyne, D.K., Landay, J.A., Hong, J.I.: The Design of Sites: Patterns, Principles, and Processes for Crafting a Customer-Centered Web Experience. Addison-Wesley, Boston (2003)Schmettow, M.: User interaction design patterns for information retrieval. In: EuroPLoP 2006, pp. 489–512 (2006)IBM big data use cases – What is a big data use case and how to get started - Exploration. http://www-01.ibm.com/software/data/bigdata/use-cases.htmlDatamer e-book: Top Five High-Impact Use Cases for Big Data Analytics (2016). https://www.datameer.com/pdf/eBook-Top-Five-High-Impact-UseCases-for-Big-Data-Analytics.pdfBig Data Uses Cases | Pentaho. http://www.pentaho.com/big-data-use-casesHenderson-Sellers, B., Ralyté, J.: Situational method engineering: state-of-the-art review. J. Univers. Comput. Sci. 16(3), 424–478 (2010)Iñiguez-Jarrin, C., García, A., Reyes, J.F., Pastor, O.: GenDomus: interactive and collaboration mechanisms for diagnosing genetic diseases. In: ENASE 2017 - Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering, Porto, Portugal, 28–29 April 2017, pp. 91–102 (2017). https://doi.org/10.5220/0006324000910102Román, J.F.R., López, Ó.P.: Use of GeIS for early diagnosis of alcohol sensitivity. In: Proceedings of the BIOSTEC 2016, pp. 284–289 (2016). https://doi.org/10.5220/0005822902840289Laskowski, N.: Ten big data case studies in a nutshell. http://searchcio.techtarget.com/opinion/Ten-big-data-case-studies-in-a-nutshellMolina, P.J., Meliá, S., Pastor, O.: JUST-UI: a user interface specification model. In: Kolski, C., Vanderdonckt, J. (eds.) Computer-Aided Design of User Interfaces III, pp. 63–74. Springer, Dordrecht (2002). https://doi.org/10.1007/978-94-010-0421-3_

A framework to identify primitives that represent usability within Model-Driven Development methods

Context: Nowadays, there are sound methods and tools which implement the Model-Driven Development approach (MDD) satisfactorily. However, MDD approaches focus on representing and generating code that represents functionality, behaviour and persistence, putting the interaction, and more specifically the usability, in a second place. If we aim to include usability features in a system developed with a MDD tool, we need to extend manually the generated code. Objective: This paper tackles how to include functional usability features (usability recommendations strongly related to system functionality) in MDD through conceptual primitives. Method: The approach consists of studying usability guidelines to identify usability properties that can be represented in a conceptual model. Next, these new primitives are the input for a model compiler that generates the code according to the characteristics expressed in them. An empirical study with 66 subjects was conducted to study the effect of including functional usability features regarding end users' satisfaction and time to complete tasks. Moreover, we have compared the workload of two MDD analysts including usability features by hand in the generated code versus including them through conceptual primitives according to our approach. Results: Results of the empirical study shows that after including usability features, end users' satisfaction improves while spent time does not change significantly. This justifies the use of usability features in the software development process. Results of the comparison show that the workload required to adapt the MDD method to support usability features through conceptual primitives is heavy. However, once MDD supports these features, MDD analysts working with primitives are more efficient than MDD analysts implementing these features manually. Conclusion: This approach brings us a step closer to conceptual models where models represent not only functionality, behaviour or persistence, but also usability features. (C) 2014 Elsevier B.V. All rights reserved.This work was developed with the support of the Spanish Ministry of Science and Innovation Project SMART ADAPT (TIN201342981-P), TIN2011-23216 and was co-financed by ERDF. It also has the support of Generalitat Valenciana-funded ORCA Project (PROMETEO/2009/015) and UV (UV-INV-PRECOMP13-115032).Panach Navarrete, JI.; Juristo, N.; Valverde Giromé, F.; Pastor López, O. (2015). A framework to identify primitives that represent usability within Model-Driven Development methods. Information and Software Technology. (58):338-354. https://doi.org/10.1016/j.infsof.2014.07.002S3383545

An empirical comparative evaluation of gestUI to include gesture-based interaction in user interfaces

[EN] Currently there are tools that support the customisation of users' gestures. In general, the inclusion of new gestures implies writing new lines of code that strongly depend on the target platform where the system is run. In order to avoid this platform dependency, gestUI was proposed as a model-driven method that permits (i) the definition of custom touch-based gestures, and (ii) the inclusion of the gesture-based interaction in existing user interfaces on desktop computing platforms. The objective of this work is to compare gestUI (a MDD method to deal with gestures) versus a code-centric method to include gesture-based interaction in user interfaces. In order to perform the comparison, we analyse usability through effectiveness, efficiency and satisfaction. Satisfaction can be measured using the subjects' perceived ease of use, perceived usefulness and intention to use. The experiment was carried out by 21 subjects, who are computer science M.Sc. and Ph.D. students. We use a crossover design, where each subject applied both methods to perform the experiment. Subjects performed tasks related to custom gesture definition and modification of the source code of the user interface to include gesture-based interaction. The data was collected using questionnaires and analysed using non-parametric statistical tests. The results show that gestUI is more efficient and effective. Moreover, results conclude that gestUI is perceived as easier to use than the code-centric method. According to these results, gestUI is a promising method to define custom gestures and to include gesture-based interaction in existing user interfaces of desktop-computing software systems. (C) 2018 Elsevier B.V. All rights reserved.This work has been supported by Department of Computer Science of the Universidad de Cuenca and SENESCYT of Ecuador, and received financial support from the Generalitat Valenciana under "Project IDEO (PROMETEOII/2014/039)" and the Spanish Ministry of Science and Innovation through the "DataMe Project (TIN2016-80811-P)".Parra-González, LO.; España Cubillo, S.; Panach Navarrete, JI.; Pastor López, O. (2019). An empirical comparative evaluation of gestUI to include gesture-based interaction in user interfaces. Science of Computer Programming. 172:232-263. https://doi.org/10.1016/j.scico.2018.12.001S23226317

Introducing Usability in a Conceptual Modeling-Based Software Development Process

Abstract. Usability plays an important role to satisfy users' needs. There are many recommendations in the HCI literature on how to improve software usability. Our research focuses on such recommendations that affect the system architecture rather than just the interface. However, improving software usability in aspects that affect architecture increases the analyst's workload and development complexity. This paper proposes a solution based on model-driven development. We propose representing functional usability mechanisms abstractly by means of conceptual primitives. The analyst will use these primitives to incorporate functional usability features at the early stages of the development process. Following the model-driven development paradigm, these features are then automatically transformed into subsequent steps of development, a practice that is hidden from the analyst

In Search of Evidence for Model-Driven Development Claims: An Experiment on Quality, Effort, Productivity and Satisfaction

Context: Model-Driven Development (MDD) is a paradigm that prescribes building conceptual models that abstractly represent the system and generating code from these models through transformation rules. The literature is rife with claims about the benefits of MDD, but they are hardly supported by evidences. Objective: This experimental investigation aims to verify some of the most cited benefits of MDD. Method: We run an experiment on a small set of classes using student subjects to compare the quality, effort, productivity and satisfaction of traditional development and MDD. The experiment participants built two web applications from scratch, one where the developers implement the code by hand and another using an industrial MDD tool that automatically generates the code from a conceptual model. Results: Outcomes show that there are no significant differences between both methods with regard to effort, productivity and satisfaction, although quality in MDD is more robust to small variations in problem complexity. We discuss possible explanations for these results. Conclusions: For small systems and less programming-experienced subjects, MDD does not always yield better results than a traditional method, even regarding effort and productivity. This contradicts some previous statements about MDD advantages. The benefits of developing a system with MDD appear to depend on certain characteristics of the development context. 2015 Elsevier B.V. All rights reserved.This work was developed with the support of the Spanish Ministry of Science and Innovation project SMART ADAPT (TIN2013-42981-P), TIN2011-23216 and was co-financed by ERDF. It also has the support of Generalitat Valenciana-funded IDEO project (PROMETEOII/2014/039) and UV (UV-INV-PRECOMP13-115032).Panach Navarrete, JI.; España Cubillo, S.; Dieste, O.; Pastor López, O.; Juristo Juzgado, N. (2015). In Search of Evidence for Model-Driven Development Claims: An Experiment on Quality, Effort, Productivity and Satisfaction. Information and Software Technology. 62:164-186. https://doi.org/10.1016/j.infsof.2015.02.012S1641866

Assessing data analysis performance in research contexts: An experiment on accuracy, efficiency, productivity and researchers' satisfaction

[EN] Any knowledge generation process involves raw data comprehension, evaluation and inferential reasoning. These practices, common to different disciplines, are known as data analysis, and represent the most important set of activities in research contexts. Researchers use data analysis software methods and tools for generating new knowledge in their daily data analysis. In recent years, data analysis software has been incorporating explicit references in modelling of cognitive processes, in order to improve the assistance offered in data analysis tasks. However, data analysis software commercial suites are still resisting this inclusion, and there is little empirical work done in knowing more about how cognitive aspects inclusion in software helps researchers in analyzing data. In this paper, we evaluate the impact produced by the explicit inclusion of cognitive processes in the assistance logic of software tools design and development. We conducted an empirical experiment comparing data analysis performance using traditional software versus data analysis performance using software-assistance tools which incorporate cognitive processes in their design. The experiment is designed in terms of accuracy, efficiency, productivity and user satisfaction during the data analysis made by researchers. It allowed us to find some clear benefits of the cognitive inclusion in the software designed for research contexts, with statistically significant differences in terms of accuracy, productivity and researcher's satisfaction in support of this explicit inclusion, although some efficiency weaknesses are detected. We also discuss the implications of these results for the priority of cognitive inclusion in the software tools design for research contexts data analysis.This paper has the support of Generalitat Valenciana through project IDEO (PROMETEOII/2014/039) and Spanish Ministry of Science and Innovation through project DataME (ref: TIN2016-80811-P).Martín-Rodilla, P.; Panach Navarrete, JI.; González-Pérez, CA.; Pastor López, O. (2018). Assessing data analysis performance in research contexts: An experiment on accuracy, efficiency, productivity and researchers' satisfaction. Data & Knowledge Engineering. 116:177-204. https://doi.org/10.1016/j.datak.2018.06.003S17720411

Including Functional Usability Features in a Model-Driven Development Method

The Software Engineering (SE) community has historically focused on working with models to represent functionality and persistence, pushing interaction modelling into the background, which has been covered by the Human Computer Interaction (HCI) community. Recently, adequately modelling interaction, and specifically usability, is being considered as a key factor for success in user acceptance, making the integration of the SE and HCI communities more necessary. If we focus on the Model-Driven Development (MDD) paradigm, we notice that there is a lack of proposals to deal with usability features from the very first steps of software development process. In general, usability features are manually implemented once the code has been generated from models. This contradicts the MDD paradigm, which claims that all the analysts effort must be focused on building models, and the code generation is relegated to model to code transformations. Moreover, usability features related to functionality may involve important changes in the system architecture if they are not considered from the early steps. We state that these usability features related to functionality can be represented abstractly in a conceptual model, and their implementation can be carried out automatically.This work has been developed with the support of MICINN (PROS-Req TIN2010-19130-C02-02, TIN2011-23216), UV (UV-INV-PRECOMP12-80627), GVA (ORCA PROMETEO /2009 /015), and co-financed with ERDF. We also acknowledge the support of the ITEA2 Call 3 UsiXML (20080026) and funding by the MITYC under the project TSI-020400-2011-20.Panach Navarrete, JI.; Juristo Juzgado, N.; Pastor López, O. (2013). Including Functional Usability Features in a Model-Driven Development Method. Computer Science and Information Systems. 10(3):999-1024. https://doi.org/10.2298/CSIS120213016PS999102410

Towards the Consolidation of Cybersecurity Standardized Definitions

[ES] La ciberseguridad es un dominio vasto y complejo, por lo que las empresas están buscando activamente soluciones eficientes en este área. Los Knowledge Graphs (KG) son uno de los mecanismos que utilizan las organizaciones para explorar la seguridad entre activos y posibles ataques. Sin embargo, la gran cantidad de información puede generar una mala interpretación de los conceptos representados en estos modelos conceptuales. Como un Knowledge Graph puede considerarse una implementación de una conceptualización, la base de los conceptos es fundamental. De ahí, el apoyo de las mejores prácticas de Modelado Conceptual, especialmente de la rama de Ontologías. En este informe se lleva a cabo un estudio piloto para descubrir el estado del arte en ”Ontologías de Ciberseguridad”. A partir de este estudio, proponemos una encuesta para ampliar nuestro enfoque terminológico. La encuesta produjo una gran cantidad de datos, por lo que desarrollamos una API REST para la manipulación de datos y una base de datos NoSQL para almacenarlos, que es la principal contribución de este documento. Nuestro objetivo es proporcionar una herramienta de análisis ontológico para ayudar a las partes interesadas a evitar malas interpretaciones durante el desarrollo y la implementación de los KG.[EN] Cybersecurity is a vast and complex domain, therefore enterprises are actively seeking efficient solutions in this matter. Knowledge Graphs (KG) are one of the mechanisms that organizations use to explore the security among assets and possible attacks. However, the great amount of information can create misinterpretation of concepts represented in these structures of conceptualizations. As a KG may be considered an implementation of a conceptualization, the grounding of concepts is fundamental. Therefore, the support of Conceptual Modeling best-practices, especially regarding the branch of Ontologies. We made a pilot study that finds out the state-of-art in ”Cybersecurity Ontologies”. From this study, we propose a survey to extend our terminological approach. The survey produced a huge amount of data, thus we develop a REST API for data manipulation and a NoSQL database to store them which is the main contribution of this document. Our goal is to provide an ontological analysis tool to help stakeholders avoid misinterpretations during KGs development and implementation.This work has been developed under the project Digital Knowledge Graph – Adaptable Analytics API with the financial support of Accenture LTD.Franco Martins Souza, B.; Serrano Gil, LJ.; Reyes Román, JF.; Panach Navarrete, JI.; Pastor López, O. (2021). Towards the Consolidation of Cybersecurity Standardized Definitions. Universitat Politècnica de València. http://hdl.handle.net/10251/16389