IMIS Institute

London, United Kingdom

IMIS Institute

London, United Kingdom
Time filter
Source Type

Paraskevopoulou M.D.,Biomedical science Research Center Alexander Fleming | Paraskevopoulou M.D.,National and Kapodistrian University of Athens | Georgakilas G.,Biomedical science Research Center Alexander Fleming | Georgakilas G.,University of Thessaly | And 9 more authors.
Nucleic Acids Research | Year: 2013

Recently, the attention of the research community has been focused on long non-coding RNAs (IncRNAs) and their physiological/pathological implications. As the number of experiments increase in a rapid rate and transcriptional units are better annotated, databases indexing IncRNA properties and function gradually become essential tools to this process. Aim of DIANA-LncBase (www. is to reinforce researchers' attempts and unravel microRNA (miRNA)-IncRNA putative functional interactions. This study provides, for the first time, a comprehensive annotation of miRNA targets on IncRNAs. DIANA-LncBase hosts transcriptome-wide experimentally verified and computationally predicted miRNA recognition elements (MREs) on human and mouse IncRNAs. The analysis performed includes an integration of most of the available IncRNA resources, relevant high-throughput HITS-CLIP and PAR-CLIP experimental data as well as state-of-the-art in silico target predictions. The experimentally supported entries available in DIANA-LncBase correspond to >5000 interactions, while the computationally predicted interactions exceed 10 million. DIANA-LncBase hosts detailed information for each miRNA-IncRNA pair, such as external links, graphic plots of transcripts' genomic location, representation of the binding sites, IncRNA tissue expression as well as MREs conservation and prediction scores. © The Author(s) 2012.

Vlachos I.S.,Institute of Molecular Oncology | Vlachos I.S.,National and Kapodistrian University of Athens | Kostoulas N.,IMIS Institute | Vergoulis T.,IMIS Institute | And 14 more authors.
Nucleic Acids Research | Year: 2012

MicroRNAs (miRNAs) are key regulators of diverse biological processes and their functional analysis has been deemed central in many research pipelines. The new version of DIANA-miRPath web server was redesigned from the ground-up. The user of DNA Intelligent Analysis (DIANA) DIANA-miRPath v2.0 can now utilize miRNA targets predicted with high accuracy based on DIANA-microT-CDS and/or experimentally verified targets from TarBase v6; combine results with merging and meta-analysis algorithms; perform hierarchical clustering of miRNAs and pathways based on their interaction levels; as well as elaborate sophisticated visualizations, such as dendrograms or miRNA versus pathway heat maps, from an intuitive and easy to use web interface. New modules enable DIANA-miRPath server to provide information regarding pathogenic single nucleotide polymorphisms (SNPs) in miRNA target sites (SNPs module) or to annotate all the predicted and experimentally validated miRNA targets in a selected molecular pathway (Reverse Search module). DIANA-miRPath v2.0 is an efficient and yet easy to use tool that can be incorporated successfully into miRNA-related analysis pipelines. It provides for the first time a series of highly specific tools for miRNA-targeted pathway analysis via a web interface and can be accessed at © 2012 The Author(s).

Vergoulis T.,IMIS Institute | Vlachos I.S.,Institute of Molecular Oncology | Vlachos I.S.,National and Kapodistrian University of Athens | Alexiou P.,Institute of Molecular Oncology | And 9 more authors.
Nucleic Acids Research | Year: 2012

As the relevant literature and the number of experiments increase at a super linear rate, databases that curate and collect experimentally verified microRNA (miRNA) targets have gradually emerged. These databases attempt to provide efficient access to this wealth of experimental data, which is scattered in thousands of manuscripts. Aim of TarBase 6.0 ( tarbase) is to face this challenge by providing a significant increase of available miRNA targets derived from all contemporary experimental techniques (gene specific and high-throughput), while incorporating a powerful set of tools in a user-friendly interface. TarBase 6.0 hosts detailed information for each miRNA-gene interaction, ranging from miRNA- and gene-related facts to information specific to their interaction, the experimental validation methodologies and their outcomes. All database entries are enriched with function-related data, as well as general information derived from external databases such as UniProt, Ensembl and RefSeq. DIANA microT miRNA target prediction scores and the relevant prediction details are available for each interaction. TarBase 6.0 hosts the largest collection of manually curated experimentally validated miRNA-gene interactions (more than 65 000 targets), presenting a 16.5-175-fold increase over other available manually curated databases. © The Author(s) 2011. Published by Oxford University Press.

Giannopoulos G.,IMIS Institute | Karagiannakis N.,IMIS Institute | Skoutas D.,IMIS Institute | Athanasiou S.,IMIS Institute
CEUR Workshop Proceedings | Year: 2015

Over the last years, thanks to Open Data initiative and the Semantic Web, there has been a vast increase on user contributed data. In several cases (e.g. Open Street Map, Geonames), the respective data include geospatial information, that is the coordinates and/or the precise geometries of buildings, roads, areas, etc. In such cases, proper schemas are defined to allow users to annotate the entities they con-tribute. However, browsing through a large and unstructured list of categories in order to select the most fitting one might be time consuming for the end users. In this paper, we present an approach for recommending categories for geospatial entities, based on previously annotated entities. Specifically, we define and implement a series of training features in order to represent the geospatial entities and capture their relation with the categories they are annotated with. These features involve spatial and textual properties of the entities. We evaluate two different approaches (SVM and kNN) on several combinations of the defined training features and we demonstrate that the best algorithm (SVM) can provide recommendations with high precision, utilizing the defined features. The aforementioned work is deployed in OSMRec, a plugin for JOSM tool for editing Open Street Map.

Maragkakis M.,Institute of Molecular Oncology | Maragkakis M.,Martin Luther University of Halle Wittenberg | Vergoulis T.,IMIS Institute | Alexiou P.,Institute of Molecular Oncology | And 8 more authors.
Nucleic Acids Research | Year: 2011

microRNAs (miRNAs) are small endogenous RNA molecules that are implicated in many biological processes through post-transcriptional regulation of gene expression. The DIANA-microT Web server provides a user-friendly interface for comprehensive computational analysis of miRNA targets in human and mouse. The server has now been extended to support predictions for two widely studied species: Drosophila melanogaster and Caenorhabditis elegans. In the updated version, the Web server enables the association of miRNAs to diseases through bibliographic analysis and provides insights for the potential involvement of miRNAs in biological processes. The nomenclature used to describe mature miRNAs along different miRBase versions has been extensively analyzed, and the naming history of each miRNA has been extracted. This enables the identification of miRNA publications regardless of possible nomenclature changes. User interaction has been further refined allowing users to save results that they wish to analyze further. A connection to the UCSC genome browser is now provided, enabling users to easily preview predicted binding sites in comparison to a wide array of genomic tracks, such as single nucleotide polymorphisms. The Web server is publicly accessible in © 2011 The Author(s).

Giannopoulos G.,IMIS Institute | Karagiannakis N.,IMIS Institute | Skoutas D.,IMIS Institute | Athanasiou S.,IMIS Institute
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016

In this paper, we present an approach for automatically recommending categories for spatiotextual entities, based on already existing annotated entities. Our goal is to facilitate the annotation process in crowdsourcing map initiatives such as OpenStreetMap, so that more accurate annotations are produced for the newly created spatial entities, while at the same time increasing the reuse of already existing tags. We define and construct a set of training features to represent the attributes of the spatiotextual entities and to capture their relation with the categories they are annotated with. These features include spatial, textual and semantic properties of the entities.We evaluate four different approaches, namely SVM, kNN, clustering+SVM and clustering+kNN, on several combinations of the defined training features and we examine which configurations of the algorithms achieve the best results. The presented work is deployed in OSMRec, a plugin for the JOSM tool that is commonly used for editing content in OpenStreetMap. © Springer International Publishing Switzerland 2016.

Giannopoulos G.,IMIS Institute | Koniaris M.,National Technical University of Athens | Weber I.,Qatar Computing Research Institute | Jaimes A.,Yahoo! Research | Sellis T.,RMIT University
Journal of Intelligent Information Systems | Year: 2014

In this paper, we introduce an approach for diversifying user comments on news articles. We claim that, although content diversity suffices for the keyword search setting, as proven by existing work on search result diversification, it is not enough when it comes to diversifying comments of news articles. Thus, in our proposed framework, we define comment-specific diversification criteria in order to extract the respective diversification dimensions in the form of feature vectors. These criteria involve content similarity, sentiment expressed within comments, named entities, quality of comments and combinations of them. Then, we apply diversification on comments, utilizing the extracted features vectors. The outcome of this process is a subset of the initial set that contains heterogeneous comments, representing different aspects of the news article, different sentiments expressed, different writing quality, etc. We perform an experimental analysis showing that the diversity criteria we introduce result in distinctively diverse subsets of comments, as opposed to the baseline of diversifying comments only w.r.t. to their content. We also present a prototype system that implements our diversification framework on news articles comments. © 2014, Springer Science+Business Media New York.

Chronis P.,IMIS Institute | Giannopoulos G.,IMIS Institute | Athanasiou S.,IMIS Institute
CEUR Workshop Proceedings | Year: 2016

In this paper we study the problem of water consumption forecasting, an instance of the general time series forecasting problem, that has not been explored adequately. We base our analysis on two types of data: aggregate and individual consumptions measured by Smart Water Meters. We evaluate a series of state of the art forecasting algorithms and showcase that these models are not suitable for every instance of the forecasting problem: while they work effectively on aggregated data that contain strong seasonal patterns, their performance drops dramatically on individual user consumption time series, where such patterns are weaker. To this end, we identify open issues and challenges on the problem and, also, demonstrate that a simpler model we propose can outperform several of the aforementioned algorithms, although still needing significant improvements. © 2016, Copyright is with the authors.

Makris K.,Technical University of Crete | Bikakis N.,National Technical University of Athens | Bikakis N.,IMIS Institute | Gioldasis N.,Technical University of Crete | Christodoulakis S.,Technical University of Crete
ACM International Conference Proceeding Series | Year: 2012

The Web of Data is an open environment consisting of very large, inter-linked RDF datasets from various domains (e.g., DBpedia, GeoNames, ACM, PubMed, etc.) accessed through SPARQL queries. Establishing interoperability in this environment has become a major research challenge. This paper presents Sparql - Rw (SPARQL - ReWriting), a framework which provides transparent query access over mapped RDF datasets. The Sparql - Rw provides a generic method for SPARQL query rewriting, with respect to a set of predefined mappings between ontology schemas. To this end, it supports a set of rich and flexible mapping types and it is proved to provide semantics preserving queries. © 2012 Authors.

Westerski A.,Technical University of Madrid | Dalamagas T.,IMIS Institute | Iglesias C.A.,Technical University of Madrid
Decision Support Systems | Year: 2013

The Idea Management Systems are a tool for collecting ideas for innovation from large communities. One of the problems of those systems is the difficulty to accurately depict the distinctive features of ideas in a rapid manner and use them for judgement of proposed innovations. Our research aims to solve this problem by introducing annotation of ideas with a domain independent taxonomy that describes various characteristics of ideas. The findings of our study show that such annotations can be successfully transformed into new metrics that allow the comparison of ideas with similar successfulness as the metrics already used in Idea Management Systems but in greater detail. The presented results are based on experiments with over 50,000 ideas gathered from case studies of four different organisations: Dell, Starbucks, Cisco and Canonical. © 2012 Elsevier B.V.

Loading IMIS Institute collaborators
Loading IMIS Institute collaborators