Un modelo de deuteroaprendizaje virtual

[Resumen] Es un hecho demostrado que los sistemas educativos vigentes no funcionan adecuadamente debido a que no tienen en cuenta las necesidades de la sociedad actual. Para conseguir solucionar este tipo de problemas, la tecnología actual se presenta como una herramienta muy versátil. Sin embargo, los sistemas de e-learning que se están utilizando, se centran en la manera de añadir la tecnología a los modelos educativos existentes. De esta manera, lo único que se consigue es trasladar al entorno telmático los mismos errores que se producen en la enseñanza tradicional. Es decir, los intentos de incluir la TIC en la educación, al no plantear una reforma completa de la forma de "enseñar", sólo consiguen destacar los errores existentes. En este trabajo, se propone la utilización de la TIC para proponer un modelo educativo que solvente este tipo de problemas. En primer lugar, se plantea el aprendizaje como la adquisición de conocimientos. Tras un estudio de las diferentes definiciones de Conocimiento, se propone una nueva definición que servirá de base para el desarrollo del soporte de la información que manejará el sistema. Como consecuencia de esto, se propone la utilización de un Sistema de Gestión de Conocimiento que, utilizando una ontología global, permita establecer la mayor cantidad de relaciones entre la información disponible, y su clasificación a diferentes niveles. Esta información se encontrará en diferentes formatos y provendrá de diversas fuentes. A partir de este soporte de conocimiento, se planteará el aprendizaje a través de la acción, que se reflejará en la ejecución de tareas, basándose en estrategias de juegos de computadora. Utilizando la filosofía de Agentes Inteligentes, el sistema interacturá con el aprendizaje para motivarlo, estimular su curiosidad y su capacidad de plantearse pregutnas, y le presentará la información personalizada y adaptada a sus preferencias

Kernel-Based Feature Selection Techniques for Transport Proteins Based on Star Graph Topological Indices

[Abstract] The transport of the molecules inside cells is a very important topic, especially in Drug Metabolism. The experimental testing of the new proteins for the transporter molecular function is expensive and inefficient due to the large amount of new peptides. Therefore, there is a need for cheap and fast theoretical models to predict the transporter proteins. In the current work, the primary structure of a protein is represented as a molecular Star graph, characterized by a series of topological indices. The dataset was made up of 2,503 protein chains, out of which 413 have transporter molecular function and 2,090 have no transporter function. These indices were used as input to several classification techniques to find the best Quantitative Structure Activity Relationship (QSAR) model that can evaluate the transporter function of a new protein chain. Among several feature selection techniques, the Support Vector Machine Recursive Feature Elimination allows us to obtain a classification model based on 20 attributes with a true positive rate of 83% and a false positive rate of 16.7%.Xunta de Galicia; 1OSIN105004P

Re-Identification of Rats with Transfer Learning

Cursos e Congresos , C-155[Abstract] The study of animal behavior in laboratory experiments is key in ethology, ecotoxicology, neuroscience and other fields. Although modern studies use computer imaging techniques, current solutions cannot preserve the identity of multiple individuals in social experiments. Thanks to the use of Transfer Learning we seek to overcome this limitations while maintaining the effectiveness of Deep Learning and reducing its computational times. With this technique we achieved promising results in the re-identification of rats after an occlusion processGrant PID2021-126289OA-I00 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe. CITIC is funded by the Xunta de Galicia through the collaboration agreement between the Consellería de Cultura, Educación, Formación Profesional e Universidades and the Galician universities for the reinforcement of the research centres of the Galician University System (CIGUS

Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning

[Abstract] In this work, we improved a previous model used for the prediction of proteomes as new B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its sequence, a known reference epitope sequence under specific experimental conditions. The peptide sequences were transformed into molecular descriptors of sequence recurrence networks and were mixed under experimental conditions. The new models were generated using 709,100 instances of pair descriptors for query and reference peptide sequences. Using perturbations of the initial descriptors under sequence or assay conditions, 10 transformed features were used as inputs for seven Machine Learning methods. The best model was obtained with random forest classifiers with an Area Under the Receiver Operating Characteristics (AUROC) of 0.981 ± 0.0005 for the external validation series (five-fold cross-validation). The database included information about 83,683 peptides sequences, 1448 epitope organisms, 323 host organisms, 15 types of in vivo processes, 28 experimental techniques, and 505 adjuvant additives. The current model could improve the in silico predictions of epitopes for vaccine design. The script and results are available as a free repositor

Improving Enzyme Regulatory Protein Classification by Means of SVM-RFE Feature Selection

[Abstract] Enzyme regulation proteins are very important due to their involvement in many biological processes that sustain life. The complexity of these proteins, the impossibility of identifying direct quantification molecular properties associated with the regulation of enzymatic activities, and their structural diversity creates the necessity for new theoretical methods that can predict the enzyme regulatory function of new proteins. The current work presents the first classification model that predicts protein enzyme regulators using the Markov mean properties. These protein descriptors encode the topological information of the amino acid into contact networks based on amino acid distances and physicochemical properties. MInD-Prot software calculated these molecular descriptors for 2415 protein chains (350 enzyme regulators) using five atom physicochemical properties (Mulliken electronegativity, Kang–Jhon polarizability, vdW area, atom contribution to P) and the protein 3D regions. The best classification models to predict enzyme regulators have been obtained with machine learning algorithms from Weka using 18 features. K* has been demonstrated to be the most accurate algorithm for this protein function classification. Wrapper Subset Evaluator and SVM-RFE approaches were used to perform a feature subset selection with the best results obtained from SVM-RFE. Classification performance employing all the available features can be reached using only the 8 most relevant features selected by SVM-RFE. Thus, the current work has demonstrated the possibility of predicting new molecular targets involved in enzyme regulation using fast theoretical algorithms.Galicia. Consellería de Economía e Industria, 10SIN105004PRInstituto de Salud Carlos III , PI13/0028

State of art: mobile software development methodolgogies

[Resumen] Desde el origen de la telefonía celular, el desarrollo de aplicaciones móviles ha crecido de manera exponencial abriendo un nuevo campo de investigación en la rama de la ingeniería de software. La necesidad de producir una aplicación con altos índices de calidad ha llevado al estudio y formulación de nuevas metodologías que abarquen todos los aspectos correspondientes y relacionados a la calidad y tiempo de producción. El objetivo de la presente investigación es realizar un estudio exhaustivo para extraer datos relevantes de cada marco de trabajo a través de la investigación bibliográfica y de campo para la construcción de un estado del arte que compruebe a través de un análisis la metodología indicada para el desarrollo de aplicaciones móviles. El resultado obtenido del análisis muestra que, a pesar de encontrar cierta similitud entre las metodologías con principios ágiles, Scrum es caracterizada como la metodología indicada para el desarrollo de aplicaciones móviles. Este hecho dio lugar al surgimiento de nuevas metodologías de desarrollo de software con enfoques a las denominadas prácticas ágiles cuyo objetivo es la producción de software de calidad.[Abstract] Since the origin of cell phones, the development of mobile applications has grown exponentially, opening a new field of research in the field of software engineering. The need to produce an application with high quality indices has led to the study and formulation of new methodologies that cover all the corresponding aspects related to quality and production time. The objective of this research is to carry out an exhaustive study to extract relevant data from each framework through bibliographic and field research for the construction of a state of the art that verifies through an analysis the methodology indicated for the development of mobile applications. The result obtained from the analysis shows that, despite finding a certain similarity between the methodologies with agile principles, Scrum is characterized as the indicated methodology for the development of mobile applications. This fact gave rise to the emergence of new software development methodologies with approaches to the so-called agile practices whose objective is the production of quality software

LECTINPred: web server that uses complex networks of protein structure for prediction of lectins with potential use as cancer biomarkers or in parasite vaccine design

Ministerio de Ciencia e Innovación; AGL2010-22290-C03-01Ministerio de Ciencia e Innovación; AGL2011-30563-C03-0

Comparison of mobile application development methodologies

[Resumen] El desarrollo de aplicaciones móviles en la actualidad tiene una gran aceptación gracias al avance de la tecnología y producción de toda clase de dispositivos que permiten a los usuarios realizar tareas cotidianas ya sean de entretenimiento o laboral. Por ende, la necesidad de producir software de calidad y para ello se han desarrollado múltiples metodologías que buscan optimizar procesos a través de buenas prácticas y principios ágiles. El objetivo de la presente investigación es realizar una búsqueda exhaustiva de las metodologías de desarrollo enfocadas a la producción aplicaciones móviles para realizar una comparación de carácter analítica y de campo. Como resultado se obtuvo que Scrum abarca gran parte de los elementos y características que beneficiarían al desarrollo de aplicaciones móviles, de igual modo en el ámbito profesional, las empresas desarrolladoras de software además de usar Mobile-D, emplean Scrum como un marco de trabajo completo que se adapta a toda clase de proyecto en cuanto al tamaño.[Abstract] The development of mobile applications is currently widely accepted thanks to the advancement of technology and the production of all kinds of devices that allow users to carry out daily tasks, whether they are entertainment or work. Therefore, the need to produce quality software and for this, multiple methodologies have been developed that seek to optimize processes through good practices and agile principles. The objective of this research is to carry out an exhaustive search of development methodologies focused on the production of mobile applications to carry out an analytical and field comparison. As a result, it was obtained that Scrum covers a large part of the elements and characteristics that would benefit the development of mobile applications, in the same way in the professional field, software development companies in addition to using Mobile-D, use Scrum as a complete framework that adapts to all kinds of projects in terms of size