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We introduce a new information and communication technology (ICT) cloud-based architecture for Global Navigation Satellite System (GNSS) high-accuracy solutions, offering also a commercial overview of GNSS downstream market to show how the developed innovation is thought to fit in the real context. The designed architecture is featured by dynamic scalability, increased integrity, and greater agility of the ICT system. The novelty of the solution developed is a customized ICT architecture, obtained through unique and privileged access to user communities in the frame of the H2020 project TREASURE, allowing the development of a solution entirely driven by user needs. The economic outlook of GNSS downstream markets evolution highlights how the technology proposed effectively matches the evolving business environment, specifically in regard to the increasing need for flexibility and competitive advantage deriving from services. The simultaneous adoption of the technical and commercial perspective is meant to offer interesting findings to both the scientific community and GNSS industry, creating synergies previously unexplored.
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We present an integrated Grid system for the prediction of protein secondary structures, based on the frequent automatic update of proteins in the training set. The predictor model is based on a feed-forward multilayer perceptron (MLP) neural network which is trained with the back-propagation algorithm; the design reuses existing legacy software and exploits novel grid components. The predictor takes into account the evolutionary information found in multiple sequence alignment (MSA); the information is obtained running an optimized parallel version of the PSI-BLAST tool, based on the MPI Master-Worker paradigm. The training set contains proteins of known structure. Using Grid technologies and efficient mechanisms for running the tools and extracting the data, the time needed to train the neural network is dramatically reduced, whereas the results are comparable to a set of well-known predictor tools.
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Internet , Modelos Químicos , Modelos Moleculares , Estructura Secundaria de Proteína , Proteínas/química , Proteínas/ultraestructura , Análisis de Secuencia de Proteína/métodos , Algoritmos , Inteligencia Artificial , Simulación por Computador , Programas Informáticos , Interfaz Usuario-ComputadorRESUMEN
This paper describes the evolution of the main services of the ProGenGrid (Proteomics & Genomics Grid) system, a distributed and ubiquitous grid environment ("virtual laboratory"), based on Workflow and supporting the design, execution and monitoring of "in silico" experiments in bioinformatics.ProGenGrid is a Grid-based Problem Solving Environment that allows the composition of data sources and bioinformatics programs wrapped as Web Services (WS). The use of WS provides ease of use and fosters re-use. The resulting workflow of WS is then scheduled on the Grid, leveraging Grid-middleware services. In particular, ProGenGrid offers a modular bag of services and currently is focused on the biological simulation of two important bioinformatics problems: prediction of the secondary structure of proteins, and sequence alignment of proteins. Both services are based on an enhanced data access service.
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Acceso a la Información , Biología Computacional , Informática Médica , Internet , Italia , Solución de Problemas , ProteómicaRESUMEN
In this paper we describe the ProGenGrid (Proteomics and Genomics Grid) system, developed at the CACT/ISUFI of the University of Lecce which aims at providing a virtual laboratory where e-scientists can simulate biological experiments, composing existing analysis and visualization tools, monitoring their execution, storing the intermediate and final output and finally, if needed, saving the model of the experiment for updating or reproducing it. The tools that we are considering are software components wrapped as Web Services and composed through a workflow. Since bioinformatics applications need to use high performance machines or a high number of workstations to reduce the computational time, we are exploiting a Grid infrastructure for interconnecting wide-spread tools and hardware resources. As an example, we are considering some algorithms and tools needed for drug design, providing them as services, through easy to use interfaces such as the Web and Web service interfaces built using the open source gSOAP Toolkit, whereas as Grid middleware we are using the Globus Toolkit 3.2, exploiting some protocols such as GSI and GridFTP.