¿Qué es la Biología de Sistemas?

There is a scene in Genesis (2, 19-20) where God grants Adam the ability to name beings and things, which is interpreted simultaneously as a power and a responsibility that the deity attributes to the human being. Defining is not easy either, to the point that some have proclaimed their hatred of definitions (Benjamin Disraeli) while others have warned us (e.g., Erasmus of Rotterdam) that every definition is dangerous. If we refer to the subject at hand, Systems Biology, the evidence of the difficulty and danger of giving a definition appears soon. Anyone who has started studying Systems Biology will have been able to see that there are not many general and comprehensive definitions of it, which is a good indicator of the difficulty and risk involved in answering the question that gives title to this article. But we will accept the challenge, aware of the risk we assume and the difficulty it entails.Hay una escena en el Génesis (2, 19-20) en la que Dios concede a Adán la capacidad de poner nombre a los seres y las cosas, lo que es interpretado al mismo tiempo como un poder y una responsabilidad que la deidad atribuye al ser humano. Definir no es fácil tampoco, hasta el punto de que algunos han proclamado su odio a las definiciones (Benjamin Disraeli) mientras que otros nos han advertido (e.g. Erasmo de Rotterdam) que toda definición es peligrosa. Si nos referimos al tema que nos ocupa, la Biología de Sistemas, la evidencia de la dicultad y del peligro que representa dar una definición aparece pronto. Cualquiera que se haya iniciado en el estudio de la Biología de Sistemas habrá podido constatar que no abundan las definiciones generales y comprensivas de la misma, lo que constituye un buen un indicador de la dificultad y el riego que implica la respuesta a la pregunta que da título a este artículo. Pero aceptaremos el reto, conscientes del riesgo que asumimos y de la dificultad que conllev

Co-evaluation in a problem solving practice in a bioscience subject

La co-evaluación o evaluación entre pares es reconocida como una actividad que estimula el papel activo del alumnado en el proceso de aprendizaje. Los estudiantes tienen la oportunidad de revisar el trabajo de su compañeros de clase frente a su propia evaluación lo que permite una reflexión sobre su proceso de aprendizaje. Como resultado, son capaces de reorientar sus propias estrategias de apredizaje. En esta comunicación se muestran los resultados de un ejercicio de co-evaluación llevado a cabo con un grupo de 90 estudiantes del Grado en Biología de la Universidad de La Laguna en el marco de un un curso general de Bioquímica con contenidos en cinética enzimática. Aunque ninguno realizó antes co-evaluaciones, los resultados muestran que las correcciones realizadas fueron correctas y consistentes con las de los profesoresCo-evaluation or evaluation between peers is gaining ground as a drive for the active role of the student in the learning process. Students are given the opportunity to review their classmate’s work, facing their own evaluation and thus reflecting of their learning process. As a result they are able to reorient their own strategy. In this communication we show the results of a co-evaluation exercise carried out with a group of 90 students of a degree in Biology, within a general course of biochemistry containing enzymology issues. Although none of them have done co-evaluations before, results show that the corrections made were refined and consistent with those made by teacher

Relevancia e impacto del perfil formativo de los estudiantes de nuevo ingreso en los grados en ciencias sobre su progreso y continuidad: un modelo predictivo

La Facultad de Ciencias de la Universidad de La Laguna lanzó, en el curso 2016/17, un Plan de detección y atención de deficiencias formativas en Biología, Física, Geología, Matemáticas y Química para el alumnado de nuevo ingreso en el centro. Esta iniciativa estuvo motivada por la constatación de que entre las diversas variables que condicionan el rendimiento académico en la universidad, la que muestra una correlación más significativa es la del rendimiento en la fase preuniversitaria. En este trabajo se hace un diagnóstico de la situación en la que se encuentra el alumnado de nuevo ingreso de la Facultad de Ciencias (Grados en Biología, Ciencias Ambientales, Física, Matemáticas y Química) y de la efec- tividad de algunas de las medidas que tradicionalmente se han venido desarro- llando para paliar los déficits formativos detectados, y se propone un modelo estadístico predictivo del rendimiento del alumnado en el primer cuatrimestre de universidad en función de su rendimiento previo, finalizando con la propuesta de una serie de políticas y acciones que desde el nivel local (centro y departamento) al institucional (universidad) habría que acometer si se quiere dar una respuesta eficaz al problema.The School of Sciences of the University of La Laguna launched, in the academic year 2016/17, a Plan for the detection and attention of training deficiencies in Biology, Physics, Geology, Mathematics and Chemistry for incoming freshmen. This initiative is motivated by the observation that among the various variables that condition the academic performance in the university, the one which correlates most significantly is the performance in the pre-university phase. In this work, a diagnosis is made of the situation in which the newly admitted students to the School of Sciences (degrees in Biology, Environmental Sciences, Physics, Mathematics and Chemistry) are, and of the effectiveness of some of the measures that have been developed so far to alleviate the learning deficits detected. Also, a predictive statistical model of student performance in the first semester of university based on their previous performance is proposed. The paper ends by suggesting a series of policies and actions that from the local level (center and department) to the institutional one (university) would have to be undertaken in order to effectively respond to the problems detected

Introducing Systems Biology to Bioscience students through mathematical modelling. A practical module

Systems Biology, one of the current approaches to the understanding of living things, aims to understand the behaviour of living systems through the creation of mathematical models that integrate the available knowledge of the system’s component parts and the relations among them. Accordingly, model building should play a central part in any biology degree program. One difficulty that we face when confronted with this task, however, is that the mathematical background of undergraduate students is very often deficient in essential concepts required for dynamic mathematical modelling. In this practical module, students are introduced to the basic techniques of mathematical modelling and computer simulation from a Systems Biology perspective

RESEARCH ARTICLE - Optimization of the citric acid production by Aspergillus niger through a metabolic flux balance model

Idiophase, the citric acid producing stage of Aspergillus niger was mathematically modeled to identify required genetic manipulations to optimize citric acid production rate. For this reason, a consistent picture of cell functioning had to be achieved. The transient idiophase nature was established by stoichiometric analysis. The main intracellular fluxes were computed by application of material and physiological constraints (ATP, reduction equivalents, proton motive force) at culture time 120 hours. The HMP pathway accounts for 16% of the glucose input (carbon basis), the Krebs cycle for 13% and the citric acid synthesis for the remaining 71%. This profile implies an operative glycerol-P shuttle. It recycles 93% of the cytosolic glycerol-P to cytosolic DHAP thus coupling the transformation of cytosolic NADH to mitochondrial FADH. A cellular maintenance energy of 3.7 mmol ATP/g·h was determined. It would be spent in fueling cytoplasmatic (1.4 mmol H+/g·h) and mitochondrial (1.8 mmol H+/g·h) H+-ATPase pumps with efficiencies of 0.65 and 1.2 mmol H+/mmol ATP respectively. The role and extent of the alternative respiration system activity and polyol excretion is accounted by the model as well. In addition, the significance of GABA shunt and futile NH4 +/NH3 cycle were rejected. According to the developed model, the specific citric productivity would be increased in 45% by an unique change if glucose influx were duplicated. Differences with predictions from other model that required many manipulations are also discussed

A predictive model of academic performance based on High School grade point average and University Access Test results

Numerosas investigaciones educativas muestran que el rendimiento académico en el primer año de universidad incide en el éxito con el que se cursan los años subsiguientes, lo que justifica el interés de analizar el rendimiento, durante el primer curso, del alumnado de nuevo ingreso e identificar los factores que influyen en él. En el presente trabajo se ha definido un nuevo indicador de este rendimiento y se han determinado, para cada uno de los grados en Ciencias de la ULL, aquellos indicadores de rendimiento previo con los que se encuentra más correlacionado el indicador introducido. Se han obtenido así sendos modelos de regresión lineal multivariante que permiten predecir el rendimiento de un estudiante de nuevo ingreso en el primer cuatrimestre del primer curso de cada grado en función de su rendimiento en Bachillerato y PAU. En todos los grados de Ciencias, la variable predictora dominante ha resultado ser la nota media de Bachillerato. La bondad de ajuste de los modelos que utilizan el nuevo indicador supera ampliamente la de otros modelos preexistentes en la literatura. El método es extensible a cualquier grado y universidad. Su aplicación sistemática permitiría definir y detectar perfiles de riesgo académico con el propósito de contribuir, por una parte, a que cada estudiante adopte una actitud proactiva hacia la subsanación de sus posibles deficiencias formativas y, por otra, a que el gestor universitario optimice los recursos humanos y materiales necesarios para mejorar el aprovechamiento académico de los estudiantes en situación de riesgo.Several educational investigations have shown that the academic performance in the first year of university affects the success in subsequent years, which justifies the interest of analyzing the performance, during the first year, of new students in order to identify the factors that influence it. In the present work, a new indicator of this performance has been defined and those indicators of previous performance which are best correlated with the indicator introduced have been determined for each one of the degrees in Science of the ULL. We have thus obtained multivariate linear regression models that allow us to predict the performance of new students in the first semester of the first year of each degree, based on their performance in High School and the University Access Test. In all of Science degrees, the dominant predictor variable has turned out to be the High School grade point average. The goodness of fit of the models that use the new indicator far exceeds that of other pre-existing models in the literature. Our method is extensible to any degree and university. Its systematic application would allow defining and detecting academic risk profiles so that, on the one hand, affected students may be encouraged to adopt a proactive attitude towards the correction of their training deficiencies and, on the other hand, university managers can optimize the human and material resources necessary to improve the academic performance of those students at risk