Cell Cycle Control in Eukaryotes: a BioSpi model

This paper presents a stochastic model of the cell cycle control in eukaryotes. The framework used is based on stochastic process algebras for mobile systems. The automatic tool used in the simulation is the BioSpi. We compare our approach with classical ODE specications

Graph embedding and geometric deep learning relevance to network biology and structural chemistry

Graphs are used as a model of complex relationships among data in biological science since the advent of systems biology in the early 2000. In particular, graph data analysis and graph data mining play an important role in biology interaction networks, where recent techniques of artificial intelligence, usually employed in other type of networks (e.g., social, citations, and trademark networks) aim to implement various data mining tasks including classification, clustering, recommendation, anomaly detection, and link prediction. The commitment and efforts of artificial intelligence research in network biology are motivated by the fact that machine learning techniques are often prohibitively computational demanding, low parallelizable, and ultimately inapplicable, since biological network of realistic size is a large system, which is characterised by a high density of interactions and often with a non-linear dynamics and a non-Euclidean latent geometry. Currently, graph embedding emerges as the new learning paradigm that shifts the tasks of building complex models for classification, clustering, and link prediction to learning an informative representation of the graph data in a vector space so that many graph mining and learning tasks can be more easily performed by employing efficient non-iterative traditional models (e.g., a linear support vector machine for the classification task). The great potential of graph embedding is the main reason of the flourishing of studies in this area and, in particular, the artificial intelligence learning techniques. In this mini review, we give a comprehensive summary of the main graph embedding algorithms in light of the recent burgeoning interest in geometric deep learning

Inferring rate coefficents of biochemical reactions from noisy data with KInfer

Dynamical models of inter- and intra-cellular processes contain the rate constants of the biochemical reactions. These kinetic parameters are often not accessible directly through experiments, but they can be inferred from time-resolved data. Time resolved data, that is, measurements of reactant concentration at series of time points, are usually affected by different types of error, whose source can be both experimental and biological. The noise in the input data makes the estimation of the model parameters a very difficult task, as if the inference method is not sufficiently robust to the noise, the resulting estimates are not reliable. Therefore "noise-robust" methods that estimate rate constants with the maximum precision and accuracy are needed. In this report we present the probabilistic generative model of parameter inference implemented by the software prototype KInfer and we show the ability of this tool of estimating the rate coefficients of models of biochemical network with a good accuracy even from very noisy input data

Cell Cycle Control in Eukaryotes: A BioSpi model

AbstractThis paper presents a stochastic model of the cell cycle control in eukaryotes. The framework used is based on stochastic process algebras for mobile systems. The automatic tool used in the simulation is the BioSpi. We compare our approach with classical ODE specifications

Competencia parental y madurez psicológica en estudiantes de secundaria de una institución educativa estatal de Trujillo

El presente estudio tiene como objetivo principal determinar la relación entre competencia parental percibida y madurez psicológica en estudiantes de secundaria de una institución educativa estatal de Trujillo, mediante el tipo de investigación no experimental de diseño correlacional, donde se contó con una muestra conformada por 178 estudiantes, varones y mujeres, entre 14 y 17 años de edad, del 3ero, 4to y 5to grado de secundaria de una institución educativa estatal de la ciudad de Trujillo, empleando como instrumentos el Cuestionario de Madurez Psicológica (PSYMAS) de Bayot y Hernández (2008) y la Escala de Competencia Parental Percibida, versión para hijos/as (ECPP-H) de Morales, Camps y Lorenzo (2012); llegando entre otras, a las siguientes conclusiones: Existe una correlación muy significativa, positiva y en grado medio, entre Competencia Parental y Madurez Psicológica en los sujetos de estudio. Así también en los estudiantes predomina un nivel medio de competencia parental y sus dimensiones; y un nivel medio de madurez psicológica y sus dimensiones.The present study has as main objective to determine the relationship between perceived parental competence and psychological maturity in high school students from a state educational institution in Trujillo, through the type of non-experimental research of correlational design, where there was a sample made up of 178 students, men and women, among 14 and 17 years of age, from 3rd, 4th and 5th grade of secondary school of a state educational institution in the city of Trujillo, using as instruments the Psychological Maturity Questionnaire (PSYMAS) by Bayot and Hernández (2008) and the Parental Competence Scale Percibida, version for children (ECPP-H) by Morales, Camps and Lorenzo (2012); reaching, among others, the following conclusions: There is a very significant, positive and average correlation between Parental Competence and Psychological Maturity in the study subjects. So also in students, a medium level of parental competence and its dimensions predominate; and a medium level of psychological maturity and its dimensions.Tesi

Dynamic Modelling of DNA Repair Pathway at the Molecular Level: A New Perspective

DNA is the genetic repository for all living organisms, and it is subject to constant changes caused by chemical and physical factors. Any change, if not repaired, erodes the genetic information and causes mutations and diseases. To ensure overall survival, robust DNA repair mechanisms and damage-bypass mechanisms have evolved to ensure that the DNA is constantly protected against potentially deleterious damage while maintaining its integrity. Not surprisingly, defects in DNA repair genes affect metabolic processes, and this can be seen in some types of cancer, where DNA repair pathways are disrupted and deregulated, resulting in genome instability. Mathematically modelling the complex network of genes and processes that make up the DNA repair network will not only provide insight into how cells recognise and react to mutations, but it may also reveal whether or not genes involved in the repair process can be controlled. Due to the complexity of this network and the need for a mathematical model and software platform to simulate different investigation scenarios, there must be an automatic way to convert this network into a mathematical model. In this paper, we present a topological analysis of one of the networks in DNA repair, specifically homologous recombination repair (HR). We propose a method for the automatic construction of a system of rate equations to describe network dynamics and present results of a numerical simulation of the model and model sensitivity analysis to the parameters. In the past, dynamic modelling and sensitivity analysis have been used to study the evolution of tumours in response to drugs in cancer medicine. However, automatic generation of a mathematical model and the study of its sensitivity to parameter have not been applied to research on the DNA repair network so far. Therefore, we present this application as an approach for medical research against cancer, since it could give insight into a possible approach with which central nodes of the networks and repair genes could be identified and controlled with the ultimate goal of aiding cancer therapy to fight the onset of cancer and its progression

Intervención arquitectónica en la Casona del Obispado de Chiclayo

En medio del área urbano monumental de la ciudad de Chiclayo se encuentra la Casona del Obispado, su construcción data a inicios del siglo XX y al igual que muchos inmuebles con valor patrimonial se encuentra en estado precario y desuso. El presente trabajo tuvo como objetivo general proponer una intervención adecuada y nuevos usos para hacer posible la reutilización y recuperación del valor patrimonial de la casona del obispado de Chiclayo, para ello se planteó una investigación con enfoque mixto, que se dividió en tres etapas, las primeras dos enfocadas en la casona, su valor patrimonial y el estado de conservación, y la última enfocada en el estudio de las características del sector urbano donde la casona se ubica. Los resultados del estudio revelaron el gran valor patrimonial que posee dentro de las dimensiones artísticas, históricas y simbólicas, a pesar del mal estado de conservación en el que se encuentra. Además, se detectaron tendencias de hibridación y compacidad en el sector y una inclinación hacia el uso comercial local. Se concluyó que la infraestructura requiere de preservación y restauración en la zona que mantiene elementos originales, el retiro de elementos agregados y la implementación de un nuevo uso comercial para generar mayor dinámica y complementar al existente

COVID-19: Relación entre comunicación y estrés laboral en el personal asistencial de los Centros de Salud-MINSA Llacuabamba y Parcoy

Con el objetivo de determinar si durante el COVID-19 existe una relación significativa entre la comunicación y el estrés laboral en el personal asistencial de los Centros de Salud-MINSA Llacuabamba y Parcoy, se desarrolló una investigación descriptivo-correlacional de diseño transversal involucrando a 53 trabajadores asistenciales entre ambas instituciones, para ello, se aplicaron dos cuestionarios estructurados encontrándose como resultados que una mayor proporción percibió a la comunicación laboral como poco adecuada (67,9%) y el nivel del estrés laboral fue predominantemente leve (43,3%). También se encontró que las dimensiones de la comunicación como dirección de la comunicación, redes de comunicación, selección del canal de comunicación y barreras de comunicación, fueron mayoritariamente poco adecuados (56,6%, 60,4% 66,0% y 60,4% respectivamente), concluyendo que durante el COVID-19 existe relación significativa (p<0,05) entre la comunicación el estrés laboral. Las dimensiones de la comunicación que se relacionan significativamente con el estrés laboral, son: dirección de la comunicación y redes de comunicación. No existe relación significativa (p>0,05) entre el estrés laboral y las dimensiones de la comunicación como la selección del canal y barreras de comunicación

Time series analysis of the Bacillus subtilis sporulation network reveals low dimensional chaotic dynamics

Chaotic behavior refers to a behavior which, albeit irregular, is generated by an underlying deterministic process. Therefore, a chaotic behavior is potentially controllable. This possibility becomes practically amenable especially when chaos is shown to be low-dimensional, i.e., to be attributable to a small fraction of the total systems components. In this case, indeed, including the major drivers of chaos in a system into the modeling approach allows us to improve predictability of the systems dynamics. Here, we analyzed the numerical simulations of an accurate ordinary differential equation model of the gene network regulating sporulation initiation in Bacillus subtilis to explore whether the non-linearity underlying time series data is due to low-dimensional chaos. Low-dimensional chaos is expectedly common in systems with few degrees of freedom, but rare in systems with many degrees of freedom such as the B. subtilis sporulation network. The estimation of a number of indices, which reflect the chaotic nature of a system, indicates that the dynamics of this network is affected by deterministic chaos. The neat separation between the indices obtained from the time series simulated from the model and those obtained from time series generated by Gaussian white and colored noise confirmed that the B. subtilis sporulation network dynamics is affected by low dimensional chaos rather than by noise. Furthermore, our analysis identifies the principal driver of the networks chaotic dynamics to be sporulation initiation phosphotransferase B (Spo0B). We then analyzed the parameters and the phase space of the system to characterize the instability points of the network dynamics, and, in turn, to identify the ranges of values of Spo0B and of the other drivers of the chaotic dynamics, for which the whole system is highly sensitive to minimal perturbation. In summary, we described an unappreciated source of complexity in the B. subtilis sporulation network by gathering evidence for the chaotic behavior of the system, and by suggesting candidate molecules driving chaos in the system. The results of our chaos analysis can increase our understanding of the intricacies of the regulatory network under analysis, and suggest experimental work to refine our behavior of the mechanisms underlying B. subtilis sporulation initiation control