Gene regulatory networks have an important role to study the behaviour of genes. By analysing
these Gene Regulatory Networks we can get the detailed information i.e. the occurrence of diseases by
changing behaviour of GRNs. Many different approaches are used (i.e. qualitative modelling and hybrid
modelling) and various tools (i.e. GenoTech, GINsim) have been developed to model and simulate gene
regulatory networks. GenoTech allows the user to specify a GRN on Graphical User Interface (GUI) according
to the asynchronous multivalued logical functions of René Thomas, and to simulate and/or analyse its
qualitative dynamical behaviour. René
Thomas discrete modelling of gene regulatory network (GRN) is a
well known approach to study the dynamics of genes. It deals with some parameters which reflect the possible
targets of trajectories. Those parameters are priory unknown. These unknown parameters are fetched using
another model checking tool SMBioNet. SMBioNet produces all the possible parameters satisfying the given
Computational Logic Tree (CTL) formula as input. This approach involving logical parameters and conditions
also known as qualitative modelling of GRN. However, this approach neglects the time delays for a gene to
pass from one level of expression to another one i.e. inhibition to activation and vice versa. To find out these
time delays, another modelling tool HyTech is used to perform hybrid modelling of GRN.
We have developed a Java based tool called GenNet http://asanian.com/gennet to facilitate the
model checking user by providing a unique GUI layout for both qualitative and quantitative modelling of GRNs.
As we discussed, three separate modelling tools are used for complete modelling and analysis of a GRN. This
process is much lengthy and takes too much time. GenNet assists the modelling users by providing some extra
features i.e. CTL editor, parameters filtering and input/output files management.
GenNet takes a GRN network as input and does all the rest of computations i.e. CTL verification,
K-parameters generation, parameter implication to GRN, state graph, hybrid modelling and parameter
filtration automatically. GenNet serves the user by computing the results within seconds that were taking hours
and days of manual computation
Distributed system is a collection of independent systems which can communicate with each other by transferring massages. There are some major issues in distributed systems but we focus in this paper on fault tolerance. It is the system’s ability to work in the condition when there occur any type of some fault in the system, like failure in communication, hardware or resources. It is a very important issue in distributed system, in this paper we present a survey of different types of fault tolerance techniques and their comparison.
Las bases de datos relacionales han sido las herramientas por excelencia para el almacenamiento de la información en los sistemas informáticos. No obstante, las bases de datos NoSQL, como tendencia, han venido ganando espacio especialmente por la escalabilidad y velocidad en sus tiempos de respuestas. PostgreSQL ha incorporado algunas características de tipo NoSQL, como el almacenamiento efímero y el manejo de datos JSON; características que pueden aprovecharse para realizar acciones desde el gestor dándole mayor potencia. El objetivo de este artículo es evaluar, mediante toda la documentación encontrada, el comportamiento de las características NoSQL de PostgreSQL frente a un gestor NoSQL, comparandola con MongoDB, respecto a los tiempos de respuestas y dar a conocer las ventajas de uno con respecto al otro.
Palabras Claves: Características NoSQL en PostgreSQL, MongoDB, PostgreSQL
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Deep learning is a fast growing field in tech that is often described to have limitless potential. This paper describes its history, why the explosion in popularity, and how it works. An example of classifying images of handwritten digits (MNIST) will be explored using a fully connected network and a convolutional neural network. Next, a brief description of the tools necessary for the reader to implement his or her own network. Finally, a view of the state of the art being developed by companies such as Google, Facebook, and Baidu.