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Vlachos I.S.,University of Thessaly | Zagganas K.,National and Kapodistrian University of Athens | Paraskevopoulou M.D.,University of Thessaly | Georgakilas G.,University of Thessaly | And 4 more authors.
Nucleic acids research | Year: 2015

The functional characterization of miRNAs is still an open challenge. Here, we present DIANA-miRPath v3.0 (http://www.microrna.gr/miRPathv3) an online software suite dedicated to the assessment of miRNA regulatory roles and the identification of controlled pathways. The new miRPath web server renders possible the functional annotation of one or more miRNAs using standard (hypergeometric distributions), unbiased empirical distributions and/or meta-analysis statistics. DIANA-miRPath v3.0 database and functionality have been significantly extended to support all analyses for KEGG molecular pathways, as well as multiple slices of Gene Ontology (GO) in seven species (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Caenorhabditis elegans, Gallus gallus and Danio rerio). Importantly, more than 600 000 experimentally supported miRNA targets from DIANA-TarBase v7.0 have been incorporated into the new schema. Users of DIANA-miRPath v3.0 can harness this wealth of information and substitute or combine the available in silico predicted targets from DIANA-microT-CDS and/or TargetScan v6.2 with high quality experimentally supported interactions. A unique feature of DIANA-miRPath v3.0 is its redesigned Reverse Search module, which enables users to identify and visualize miRNAs significantly controlling selected pathways or belonging to specific GO categories based on in silico or experimental data. DIANA-miRPath v3.0 is freely available to all users without any login requirement. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.


Holland O.,King's College London | Aijaz A.,King's College London | Kaltenberger F.,Eurecom | Foukalas F.,Athena Research and Innovation Center | And 3 more authors.
IEEE Communications Magazine | Year: 2016

Mobile networks will increasingly need to make use of heterogeneous access and spectrum opportunities to realize required capacity and quality of service. Moreover, aggregation of such resources will routinely be necessary, and there will be a clear need to develop a management architecture for that aggregation. Such an architecture should ascertain what can and should be aggregated by particular systems, networks, and terminals in view of better managing the collection of available resources on a heterogeneous system level, taking into account all systems', networks', and terminals' traffic requirements and technical capabilities. This article proposes such a management architecture and assesses its benefits, quantified by some particular examples. © 1979-2012 IEEE.


Vlachos I.S.,University of Thessaly | Vlachos I.S.,National and Kapodistrian University of Athens | Paraskevopoulou M.D.,University of Thessaly | Karagkouni D.,University of Thessaly | And 11 more authors.
Nucleic Acids Research | Year: 2015

MicroRNAs (miRNAs) are short non-coding RNA species, which act as potent gene expression regulators. Accurate identification of miRNA targets is crucial to understanding their function. Currently, hundreds of thousands of miRNA:gene interactions have been experimentally identified. However, this wealth of information is fragmented and hidden in thousands of manuscripts and raw nextgeneration sequencing data sets. DIANA-TarBase was initially released in 2006 and it was the first database aiming to catalog published experimentally validated miRNA:gene interactions. DIANA-TarBase v7.0 (http://www.microrna.gr/tarbase) aims to provide for the first time hundreds of thousands of high-quality manually curated experimentally validated miRNA:gene interactions, enhanced with detailed meta-data. DIANA-TarBase v7.0 enables users to easily identify positive or negative experimental results, the utilized experimental methodology, experimental conditions including cell/tissue type and treatment. The new interface provides also advanced information ranging from the binding site location, as identified experimentally as well as in silico, to the primer sequences used for cloning experiments. More than half a million miRNA:gene interactions have been curated from published experiments on 356 different cell types from 24 species, corresponding to 9- to 250-fold more entries than any other relevant database. DIANA-TarBase v7.0 is freely available. © The Author(s) 2014.


PubMed | National Technical University of Athens, National and Kapodistrian University of Athens, Athena Research and Innovation Center and University of Thessaly
Type: Journal Article | Journal: Nucleic acids research | Year: 2015

microRNAs (miRNAs) are short non-coding RNA species, which act as potent gene expression regulators. Accurate identification of miRNA targets is crucial to understanding their function. Currently, hundreds of thousands of miRNA:gene interactions have been experimentally identified. However, this wealth of information is fragmented and hidden in thousands of manuscripts and raw next-generation sequencing data sets. DIANA-TarBase was initially released in 2006 and it was the first database aiming to catalog published experimentally validated miRNA:gene interactions. DIANA-TarBase v7.0 (http://www.microrna.gr/tarbase) aims to provide for the first time hundreds of thousands of high-quality manually curated experimentally validated miRNA:gene interactions, enhanced with detailed meta-data. DIANA-TarBase v7.0 enables users to easily identify positive or negative experimental results, the utilized experimental methodology, experimental conditions including cell/tissue type and treatment. The new interface provides also advanced information ranging from the binding site location, as identified experimentally as well as in silico, to the primer sequences used for cloning experiments. More than half a million miRNA:gene interactions have been curated from published experiments on 356 different cell types from 24 species, corresponding to 9- to 250-fold more entries than any other relevant database. DIANA-TarBase v7.0 is freely available.


PubMed | National Technical University of Athens, Athena Research and Innovation Center, National and Kapodistrian University of Athens and University of Thessaly
Type: Journal Article | Journal: Nucleic acids research | Year: 2016

microRNAs (miRNAs) are short non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of coding gene expression. Long non-coding RNAs (lncRNAs) have been recently reported to interact with miRNAs. The sponge-like function of lncRNAs introduces an extra layer of complexity in the miRNA interactome. DIANA-LncBase v1 provided a database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs. The second version of LncBase (www.microrna.gr/LncBase) presents an extensive collection of miRNA:lncRNA interactions. The significantly enhanced database includes more than 70 000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries. The new experimental module presents a 14-fold increase compared to the previous release. LncBase v2 hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm. The relevant module provides millions of predicted miRNA binding sites, accompanied with detailed metadata and MRE conservation metrics. LncBase v2 caters information regarding cell type specific miRNA:lncRNA regulation and enables users to easily identify interactions in 66 different cell types, spanning 36 tissues for human and mouse. Database entries are also supported by accurate lncRNA expression information, derived from the analysis of more than 6 billion RNA-Seq reads.


PubMed | National Technical University of Athens, University of Peloponnese, Athena Research and Innovation Center and University of Thessaly
Type: Journal Article | Journal: Nucleic acids research | Year: 2016

microRNAs (miRNAs) are small non-coding RNAs that actively fine-tune gene expression. The accurate characterization of the mechanisms underlying miRNA transcription regulation will further expand our knowledge regarding their implication in homeostatic and pathobiological networks. Aim of DIANA-miRGen v3.0 (http://www.microrna.gr/mirgen) is to provide for the first time accurate cell-line-specific miRNA gene transcription start sites (TSSs), coupled with genome-wide maps of transcription factor (TF) binding sites in order to unveil the mechanisms of miRNA transcription regulation. To this end, more than 7.3 billion RNA-, ChIP- and DNase-Seq next generation sequencing reads were analyzed/assembled and combined with state-of-the-art miRNA TSS prediction and TF binding site identification algorithms. The new database schema and web interface facilitates user interaction, provides advanced queries and innate connection with other DIANA resources for miRNA target identification and pathway analysis. The database currently supports 276 miRNA TSSs that correspond to 428 precursors and >19M binding sites of 202 TFs on a genome-wide scale in nine cell-lines and six tissues of Homo sapiens and Mus musculus.


Mavrotas G.,National Technical University of Athens | Skoulaxinou S.,EPEM SA | Gakis N.,FACETS SA | Katsouros V.,Athena Research and Innovation Center | Georgopoulou E.,National Observatory of Athens
Waste Management | Year: 2013

In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH4 generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application of the model in a Greek region. © 2013 Elsevier Ltd.


Mavrotas G.,National Technical University of Athens | Gakis N.,FACETS SA | Skoulaxinou S.,EPEM SA | Katsouros V.,Athena Research and Innovation Center | Georgopoulou E.,National Observatory of Athens
Renewable and Sustainable Energy Reviews | Year: 2015

Energy production from Municipal Solid Waste (MSW) has become one of the most prominent strategies in MSW management. In this study a multi-objective mathematical programming model is developed in order to provide the candidate (Pareto optimal) solutions for a MSW management system performing structural, design and operational optimization. Besides the economic criterion the Green House Gas (GHG) emissions are taken into account as a second optimization criterion. Therefore, we do not obtain just an optimal solution (i.e. least cost), but a set of Pareto optimal solutions that spread from minimum cost to minimum GHG emissions. Each Pareto optimal solution provides the corresponding technologies and the capacities that are associated with it. An innovative issue is that we incorporate the external costs/benefits associated with (a) atmospheric pollution impacts (b) impacts on soil and groundwater (c) impacts on quality of life (d) electricity use/displacement (e) fertilizer use reduction from compost. Using the external costs/benefits as an additional term in the cost objective significantly affects the results especially regarding the Waste-to-Energy options. This is clearly illustrated in the case study for the MSW management of the Athens region in Greece. © 2015 Elsevier Ltd. All rights reserved.


Liakos P.,Athena Research and Innovation Center | Koltsida P.,Athena Research and Innovation Center | Kakaletris G.,Athena Research and Innovation Center | Baumann P.,Jacobs University Bremen
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2015

The ever growing amount of information collected by scientific instruments and the presence of descriptive metadata accompanying them calls for a unified way of querying over array and semi-structured data. We present xWCPS, a novel query language that bridges the path between these two different worlds, enhancing the expressiveness and user-friendliness of previous approaches. © Springer International Publishing Switzerland 2015.


Katsouros V.,Athena Research and Innovation Center | Koulamas C.,Athena Research and Innovation Center | Fournaris A.P.,Athena Research and Innovation Center | Emmanouilidis C.,Athena Research and Innovation Center
IFAC-PapersOnLine | Year: 2015

The increasingly internetworked nature of physical entities and industrial assets is the result of deeper penetration of Internet of Things technologies (IoT) in production environments. Such technologies empower physical product and asset entities to become not only production but also information actors. The physical IoT entities may thus exhibit various levels of intelligence, supported by internet-working, web-based programming and advanced data processing capabilities. At the lower information processing level of physical assets, IoT-enabled entities are now highly integrated with the physical products and assets, forming what is often termed as Cyber-Physical Systems (CPS). They contribute to the upgrade of conventional assets to intelligent ones. For an asset to exhibit intelligent behaviour mere data exchange does not suffice and some form of self-awareness is needed. This paper presents the development of a methodology for embedding event detection to support self-awareness, leading to safer asset operation. Based on wireless sensors, as well as on embedded intelligence, an awareness-enabled asset is a dual entity, consisting of its physical, as well as well its cyber counterpart. This CPS entity is not only capable of performing its intended physical function as part of a production process, but is also capable of handling sensorial monitoring information, process it and perform detection in sensor nodes. The methodology is demonstrated in a lifts monitoring piloting case. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

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